# Aesthetics of Sanskrit Poetry from the Perspective of Computational
Linguistics: A Case Study Analysis on Śikṣāṣṭaka

Jivnesh Sandhan1, Amruta Barbadikar2, Malay Maity2, Pavankumar Satuluri3,
Tushar Sandhan1, Ravi M. Gupta4, Pawan Goyal5 and Laxmidhar Behera1,6
1IIT Kanpur, 2University of Hyderabad, 3IIT Roorkee,
4Utah State University, 5IIT Kharagpur, 6IIT Mandi
jivneshsandhan<EMAIL_ADDRESS>
###### Abstract

Sanskrit poetry has played a significant role in shaping the literary and
cultural landscape of the Indian subcontinent for centuries. However, not much
attention has been devoted to uncovering the hidden beauty of Sanskrit poetry
in computational linguistics. This article explores the intersection of
Sanskrit poetry and computational linguistics by proposing a roadmap of an
interpretable framework to analyze and classify the qualities and
characteristics of fine Sanskrit poetry. We discuss the rich tradition of
Sanskrit poetry and the significance of computational linguistics in
automatically identifying the characteristics of fine poetry. We also identify
various computational challenges involved in this process, including
subjectivity, rich language use, cultural context and lack of large labeled
datasets. The proposed framework involves a human-in-the-loop approach that
combines deterministic aspects delegated to machines and deep semantics left
to human experts.

We provide a deep analysis of Śikṣāṣṭaka, a Sanskrit poem, from the
perspective of 6 prominent kāvyaśāstric schools, to illustrate the proposed
framework. Additionally, we provide compound, dependency, anvaya (prose order
linearised form), meter, rasa (mood), alaṅkāra (figure of speech), and rīti
(writing style) annotations for Śikṣāṣṭaka and a web application to illustrate
the poem’s analysis and annotations. Our key contributions include the
proposed framework, the analysis of Śikṣāṣṭaka, the annotations and the web
application111Link for interactive analysis of Śikṣāṣṭaka:
https://sanskritshala.github.io/shikshastakam/ for future research. We aim to
bridge the gap between kāvyaśāstra and computational methods and pave the way
for future research.

##  1 Introduction

Sanskrit literature has a rich and diverse tradition that has played a
significant role in shaping the literary and cultural landscape of the Indian
subcontinent for centuries Pollock (2006); Jamison and Brereton (2014). With
its complex grammatical rules and nuanced vocabulary, the Sanskrit language
has provided a fertile ground for poets to craft intricate and evocative
stanzas that capture the key elements of human experience Pollock (1996). From
the ancient epics like the Rāmāyaṇa and the Mahābhārata, to the lyrical works
of Kālidasa and Bhartṛhari etc. Sanskrit poetry has embodied the key elements
of Indian thought and culture, providing inspiration and contemplation for
generations of readers and scholars. However, the researchers in the
computational linguistics community have not devoted much attention to
uncovering the hidden beauty in Sanskrit poetry Scharf et al. (2015).

The computational linguistic research community could be interested in
identifying fine poetry for various reasons, including the need to evaluate
machine-generated poetry Agarwal and Kann (2020); Van de Cruys (2020); Li et
al. (2020); Hopkins and Kiela (2017), translating poetry Yang et al. (2019);
Ghazvininejad et al. (2018); Krishna et al. (2019), to gain a deeper
understanding of poetic language Haider (2021); Hämäläinen and Alnajjar
(2019); Waltz (1975), and to develop recommender systems Zhang et al. (2020);
Foley IV (2019) for readers interested in poetry. By analyzing large corpora
of poetry Haider (2021); Haider et al. (2020); Gopidi and Alam (2019); Fairley
(1969) and identifying the most outstanding examples, researchers can improve
evaluation metrics for machine-generated poetry Yi et al. (2018); Liu et al.
(2019); Ghazvininejad et al. (2017); Gonçalo Oliveira (2017), develop new
models and techniques for natural language processing Hu and Sun (2020), and
preserve cultural heritage. Furthermore, personalized recommendations for
readers can be developed based on their preferences.

Analyzing and identifying the characteristics of fine poetry automatically
presents several computational challenges, including: (1) Subjectivity: The
perception of what makes a poem “good" is subjective and can vary widely among
individuals and cultures Sheng and Uthus (2020). Developing a computational
model that can accurately capture and evaluate the aesthetic qualities of a
poem is therefore challenging. (2) Rich language use: Poetry often employs
complex language use, including metaphors, similes, allusions, and wordplay,
which can be difficult for computational models to understand and generate
Chakrabarty et al. (2021). (3) Cultural context: Poetry is often deeply rooted
in cultural and historical contexts Gopidi and Alam (2019), which can be
challenging for automated systems to comprehend and incorporate. (4) Lack of
large labeled datasets: The development of automated systems to identify the
characteristics of fine poetry relies on large, labeled datasets, which can be
difficult to create due to the subjective nature of poetry and the diversity
of cultural and linguistic contexts Al-Ghamdi et al. (2021); Horváth et al.
(2022). Overall, the computational challenges of identifying the
characteristics of fine poetry automatically include the development of
sophisticated algorithms that can account for the subjective nature of poetry,
understand complex language use, incorporate cultural context and work with
limited labeled data.

In this article, we aim to address the question of whether we can build an
automated and interpretable framework to analyze and classify Sanskrit poetry
(kāvya) Kesarwani et al. (2017) into levels of the characteristics of fine
composition. This framework has the potential to answer interesting questions
such as given two kāvyas, which one is more beautiful and why. It could also
serve as a valuable tool for pedagogical purposes. The kāvyaśāstra provides
various perspectives for the analysis of poetry, and we select a Śikṣāṣṭaka
composition222Refer to the actual piece and its translation in Appendix A. to
analyze from these different perspectives. We also aim to discuss whether
computational methods can aid in similar analysis and the limitations of
existing state-of-the-art methods. Our proposed framework involves a human-in-
the-loop approach Zhipeng et al. (2019); Ghazvininejad et al. (2017), where
deterministic aspects are delegated to machines, and deep semantics are left
to human experts. We hope that with further development, this framework can
eventually become fully automated, enhancing the appreciation of Sanskrit
poetry’s inner beauty for neophytes and Sanskrit enthusiasts alike. We believe
that this work can serve as a stepping stone, bridging the gap between the
tradition of kāvyaśāstra and computational methods, and paving the way for
future research.

Our key contributions are as follows:

  1. 1.

We propose a roadmap of human-in-loop and interpretable framework to classify
Sanskrit poetry into levels of the characteristics of fine composition (§4).

  2. 2.

We illustrate the proposed framework by providing a deep analysis of
Śikṣāṣṭaka from the perspective of 6 prominent kāvyaśāstra schools (§3).

  3. 3.

We provide compound, dependency, anvaya, meter, rasa, alaṅkāra, rīti
annotations for Śikṣāṣṭaka (§5).

  4. 4.

We also provide web application333Link for interactive analysis of Śikṣāṣṭaka:
https://sanskritshala.github.io/shikshastakam/ to illustrate our Śikṣāṣṭaka
analysis and annotations (§5).

  5. 5.

We publicly release our codebase of framework and web-application for future
research444https://github.com/sanskritshala/shikshastakam

##  2 Background

School Founder Treatise Objective English meaning rasa Bharatamunī nāṭyaśāstra
na hi rasadṛte kaścidarthaḥ pravartate No meaning proceeds, if a poetry does
not carries rasa. alaṅkāra Bhāmaha Kāvyālaṅkāra rūpakādiralaṃkāraḥ
tasyānyairvahudhoditaḥ na kāntamapi nirbhūṣaṃ vibhāti vanitāmukham Alaṅkāras
are vital for poetic beauty, just like ornaments for a charming woman’s face.
rīti Vāmana Kāvyālaṅkāra-sūtravṛtti rītirātmā kāvyasya Poetic style (rīti) is
the soul of poetry. dhvani Ānandavardhana Dhvanyāloka kāvyasyātmā dhvaniḥ
dhvani is the soul of poetry. vakrokti Kuntaka vakrokti-jīvitam vakroktiḥ
kāvyajīvitam vakrokti is the vital element of the poetry. aucitya Kṣemendra
aucitya-vicāra-carcā aucityaṃ rasasiddhasya sthiraṃ kāvyasya jīvitam Propriety
is the stable vital element of the poetry full of rasa.

Table 1: Chronological overview of 6 schools of kāvyaśāstra with founder
ācārya, their treatise and objectives.

#### The 6 main schools of kāvyaśāstra (Poetics):

kāvyaśāstra is the traditional Indian science of poetics and literary
criticism, which has played a significant role in shaping the development of
literature and aesthetics in the Indian subcontinent for over two thousand
years. The term “kāvya” refers to poetry or literature, while “Śāstra” means
science or knowledge, and kāvyaśāstra is thus the systematic study of the
nature, forms, and principles of poetry and literature. The roots of
kāvyaśāstra can be traced back to ancient India, where it developed alongside
other branches of learning such as philosophy, grammar, and rhetoric. Over
time, kāvyaśāstra evolved into a complex and sophisticated system of poetics,
encompassing a wide range of concepts and techniques for analyzing and
appreciating poetry, such as rasa (mood of poetry), alaṅkāra (the use of
rhetorical and figurative devices), dhvani (superiority of suggestive
meaning), vakrokti (oblique), aucitya (appropriateness) and rīti (style of
writing).

#### chandaśśāstra

is the traditional Indian science of meter and versification in poetry, dating
back to the Vedic period. It involves the systematic study of the principles,
forms, and structures of meter and versification in poetry, including the use
of various poetic devices and the study of various types of meters and poetic
forms. While closely related to kāvyaśāstra, chandaśśāstra is a separate
branch of traditional Indian knowledge and is not considered one of the 6 main
schools of kāvyaśāstra. Key concepts and techniques include the classification
of meters, rhyme and alliteration, and the principles of accentuation and
stress. chandaśśāstra has played a significant role in the development of
Indian poetics and literary theory, and continues to be a vital part of Indian
cultural heritage. By mastering the principles of chandaśśāstra, poets and
writers can create verses that are both aesthetically pleasing and technically
precise, resulting in some of the most beautiful and evocative poetry in the
world.

#### Efforts put in Computational Linguistics:

In the field of computational poetry, researchers have tackled various
problems using algorithms and computational methods, such as generating new
poetry Agarwal and Kann (2020); Van de Cruys (2020); Li et al. (2020); Hopkins
and Kiela (2017); Krishna et al. (2020), translating poetry Yang et al.
(2019); Ghazvininejad et al. (2018) analyzing emotional tone, analyzing rhyme
and meter patterns Kao and Jurafsky (2012); Greene et al. (2010); Fang et al.
(2009), classifying poetry Baumann et al. (2018); Kesarwani et al. (2017), and
recommending poetry Zhang et al. (2020); Foley IV (2019). However, existing
work does not focus much on analyzing the characteristics of fine poetry,
which is crucial for improving the generation, translation, and recommendation
applications. This gap motivates our work, which proposes an interpretable
framework to classify Sanskrit poetry into different levels of composition
using computational linguistics. We demonstrate the proposed framework by
conducting a deep analysis of Śikṣāṣṭaka, a Sanskrit poem, from the
perspective of 6 well-known kāvyaśāstric schools. The key contributions of our
article include the proposed framework, the analysis of Śikṣāṣṭaka, the
annotations, the web application, and the publicly released codebase for
future research.

##  3 Basics of schools, Computational Aspect, Open Issues and Analysis

This section presents the basics of the 7 schools of kāvyaśāstra and
chandaśśāstra. Each subsection provides a comprehensive overview of the
respective school’s fundamentals, the feasibility of developing a
computational system, open issues and future directions. We provide reasoning
for choosing the Śikṣāṣṭaka and demonstrate its analysis based on the
corresponding school.

#### Why Śikṣāṣṭaka:

To facilitate a more thorough and nuanced analysis of kāvya, we set a few
criteria to guide our selection of the most appropriate composition for our
study. These criteria are as follows: (1) the composition should be
sufficiently small to enable comprehensive scrutiny from diverse kāvyaśāstra
perspectives; (2) the poet who has authored the composition ought not to
possess a significant reputation in the kāvyaśāstra domain to obviate the
potential for biases that may arise from establishing the composition as
uttama kāvya; (3) the composition should have made a substantive contribution
to the traditions from a non-literary perspective to explore the role of
kāvyaśāstra aspects in its accomplishment.

The Śikṣāṣṭaka composition is well-suited for our analysis as it satisfies all
three criteria that we have established. First, it meets the requirement of
being compact enough to allow for in-depth examination from various
kāvyaśāstra perspectives as it consists of only eight stanzas.555We encourage
readers to go through this composition:
https://sanskritshala.github.io/shikshastakam/shloka.html where word-to-word
meanings and translations are given. Additionally, not all aṣṭakas can be
considered uttama kāvya (the fine poetry), which further supports its
appropriateness as a subject of study. Second, the author of Śikṣāṣṭaka,
Caitanya Mahāprabhu, is not primarily known as a poet or literary figure.
Thus, he meets the second criterion of not being a well-established poet in
the kāvyaśāstra domain, which helps to minimize the potential biases that
could arise from claiming the composition as uttama kāvya. Finally, Śikṣāṣṭaka
has made significant contributions to the traditions of Gauḍīya Vaiṣṇavism
from a non-literary perspective, which satisfies the third criterion. This
composition has significantly influenced the lifestyle of the religious
community adhering to the principles of Gaudiya Vaishnavism, serving as the
fundamental backbone of their philosophy for the past 500 years. The enduring
prevalence and practice of these teachings within the community underscore the
profound impact of this composition on their way of life. In summary, the
Śikṣāṣṭaka composition satisfies all three criteria.

###  3.1 Metrical analysis

#### Basics:

The bulk of Sanskrit literature consists of poetic works that conform to the
conventions of Sanskrit prosody, or chandaśśāstra, which involves the study of
Sanskrit meters, or chandas. The primary objective of utilizing chandas is to
infuse rhythm into the text to facilitate memorization, while also aiding in
the preservation of accuracy to some degree DEO (2007); Melnad et al. (2015).
Piṅgala is considered to be the father of chandaśśāstra. Prominent scholars
and their work in this field include Piṅgala (Chandaśśūtra), Bharata Munī
(nāṭyaśāstra), Piṅgala Bhaṭṭa (Chandomanjarī), Vṛttanātha (Vṛttaratnākara),
Jagannātha Paṇḍita (rasagaṅgādhara), etc. Although approximately 1,398 meters
are described in Vṛttaratnākara Rajagopalan (2018), not all are widely used.

#### Computational aspect:

In chandaśāstra, the classification of each syllable (akṣara) in Sanskrit as
either laghu (short) or guru (long) enables the representation of every line
of Sanskrit text as a binary sequence comprised of laghu and guru markers. The
identification of specific patterns within these sequences leads to the
recognition of various types of chandas, thus enabling the deterministic
identification of a meter. In recent years, commendable efforts have been made
by the computational community to develop user-friendly toolkits for meter
identification Neill (2023); Rajagopalan (2018); Terdalkar and Bhattacharya
(2023).

####  Śikṣāṣṭaka analysis:

The aṣṭaka, which comprises a series of 8 stanzas, is typically composed in a
single meter. In the case of the Śikṣāṣṭaka, there are 5 meters employed,
namely, śārdūlavikrīḍita, vasantatilaka, anuṣṭup, viyoginī and upajāti
(indravaṁśa and vaṃśastha). Further details on how to identify meters can be
found in the relevant literature Neill (2023); Rajagopalan (2018); Terdalkar
and Bhattacharya (2023). The identification of meters has aided in the
identification of typographical errors (tanuja $\rightarrow$ tanūja,
dhūli$\rightarrow$ dhūlī, gadagada$\rightarrow$ gadgada) in some of the
existing manuscripts of the Śikṣāṣṭaka. One may wonder about the use of 5
different meters in the Śikṣāṣṭaka. Some scholars, or ācāryas, have argued
that the stanzas were not composed in a single sitting. Rather, they were
collected in Rupa Goswami’s (disciple of the author of Śikṣāṣṭaka) Padyāvalī,
which is an anthology of compositions by expert poets in the gauḍīya Vaiṣṇava
tradition. Kṛṣṇadas Kaviraj Goswami later compiled and arranged them in a
meaningful order in his composition, the Caitanya Caritāmṛta. We posit that
the use of multiple meters serves as an evidence supporting this claim.

#### Open issues and future direction:

It would be interesting to explore the correlation between the intrinsic mood
of the meter and the mood of the poetry. It would also be worthwhile to
investigate the relationship between poets and the meters they have employed.
This could involve examining patterns in their favorite choices and attempting
to identify the poet based on the composition itself. Additionally, there is
potential for exploring whether the occurrence of rasadoṣa (obstruction in the
enjoyment of mellow) can be predicted through automatic identification of the
composition’s chandas. These investigations could contribute to a deeper
understanding of the relationship between meters, poetry, and emotion in
Sanskrit literature.

###  3.2 alaṅkāra school

#### Basics:

This school focuses on the use of figurative language or literary devices to
enhance the beauty and aesthetic appeal of poetry. It includes the study of
metaphors, similes, personification, hyperbole, and other literary devices.
The most important exponent of this school is Bhāmaha, who wrote the
kāvyālaṅkāra, one of the earliest treatises on poetic embellishments. Other
notable figures associated with this school include Daṇḍin, Udbhaṭa, Rudraṭa
and so on. There are two broad categories of alaṅkāras: (1) śabdālaṅkāra:
refers to the figure of sound that relies on the pleasing sound or choice of
words, which loses its effect when the words are substituted with others of
similar meaning. (2) arthālaṅkāra: is the figure of speech that is based on
the meaning of words.

#### Computational aspect:

The process of identifying śabdālaṅkāra is considered deterministic and
involves verifying the occurrence of specific patterns of syllables or words.
In contrast, the identification of arthālaṅkāra presents a significant
semantic challenge, even for experienced annotators. The feasibility and
difficulty of developing supervised systems for this purpose can be better
understood through empirical investigations. There is no system currently
available for automated alaṅkāra analysis for Sanskrit. To develop a
supervised data-driven system, several important questions must be addressed.
For instance, it is crucial to determine the amount of data that needs to be
annotated, as well as the appropriate methods for marking alaṅkāra
annotations, such as whether they should be marked at the level of a complete
śloka and a phrase. To address these concerns, it is necessary to develop a
standardized scheme for alaṅkāra annotation. This would enable researchers to
collect and analyze annotated data consistently and systematically, which
would facilitate the development of accurate and reliable automated systems
for alaṅkāra analysis.

####  Śikṣāṣṭaka analysis:

In our analysis of the Śikṣāṣṭaka, we have employed the alaṅkāra
categorization outlined by Mammaṭa in his influential work “Kāvyaprakāśa".
This text provides a comprehensive overview of 67 alaṅkāras or literary
ornaments that can be utilized to embellish and enhance the expression of
poetry. According to the alaṅkāra school, alaṅkāra is considered the soul of
poetry, and without its incorporation, a poetic composition lacks vitality. In
other words, kāvya without alaṅkāra is likened to a lifeless entity, deemed by
some poets of this school to be comparable to a widow.666alaṅkārarahitā
vidhavaiva sarasvatī— 2.334, Agnipurāṇa
A poetry which is also a form of goddess Sarasvaī, is not decorated by
alaṅkāras, looks like a widow women, who is not wearing any ornaments.
Furthermore, it is worth noting that certain poets from this tradition place
greater emphasis on arthālaṅkāra, or figurative language, over śabdālaṅkāra,
which deals primarily with sound patterns and word repetition. The Śikṣāṣṭaka,
a devotional composition in Sanskrit, exhibits the mood of separation
(vipralambha-śṛṅgāraḥ) as its primary rasa or mood. The author portrays
himself as a devotee, and his beloved is Lord Govinda. The appropriate use of
alaṅkāras (figures of speech) in this composition serves to express the rasa
without hindrance. The author employs śabdālaṅkāras
(anuprāsa777varṇasāmyamanuprāsaḥ— 9.79, Kāvyaprakāśa
The similarity in the letters used in the poetry is ‘Anuprāsa’. It is similar
to the alliteration in the English language.) and arthālaṅkāras
(rūpaka888tadrūpakambhedo yaḥ upamānopameyayoḥ— 10.93, Kāvyaprakāśa
Rūpaka is a figure of speech, where the upameya, which is being compared and
the upamāna with which is compare are explained as if both are not different
from each other. It is similar to the metaphor., upamā999sādharmyamupamā
bhede—1.87, Kāvyaprakāśa
When the upameya and the upamāna are not compared based on the similarity
possessed by the both is called as Upamā. It is similar to the simile.,
vyatireka101010upamānād yadanyasya vyatirekaḥ saḥ eva saḥ, 10.105,
Kāvyaprakāśa
If the upameya is said to be having a higher degree of quality than the
upamāna, then it is called as vyatireka alaṅkāra., tulyayogitā111111niyatānāṁ
sakṛddharmaḥ sā punaḥ tulyayogitā— 10.104, Kāvyaprakāśa
A single mention of a property belonging to various other things is
Tulyayogitā and viśeṣokti121212viśeṣoktirakhaṇḍeṣu kāraṇeṣu phalāvacaḥ—
10.108, Kāvyaprakāśa
The condition in which various reasons are stated but the result is not seen
is called viśeṣokti. There are two types of this figure of speech. 1) - when
the reason is specified for the unseen effect it is uktanimitta-viśeṣokti
otherwise it is anuktanimitta-viśeṣokti. ) in Śikṣāṣṭaka. The use of rūpaka
(metaphor) and upamā is frequent, with the former appearing 6 times and the
latter 4 times. The metaphors are employed to equate two things directly,
while similes use “like" or “as" to make comparisons.

In the first stanza, the author uses a series of 5 metaphors to describe the
victory of Śrikṛṣṇa Saṅkīrtana. The use of these metaphors creates a garland-
like effect, which serves as an offering to acknowledge the victory of
Śrīkṛṣṇa Saṅkīrtana. Additionally, the use of antyānuprāsa Śabdalaṅkāra (a
figure of speech where every word ends with a similar suffix) creates a
rhythmic effect. In the second stanza, the author expresses his sorrow of not
having an attachment to such a glorious Saṅkīrtana, where the Lord invests all
his potencies without keeping any rules and regulations. Although there is
every reason to get attached to such Saṅkīrtana, the author cannot get
attached, which is expressed through Uktanimitta viṡeṣyokti alaṅkāra. This
alaṅkāra is used to denote that all the causes are present for action to
happen, yet the action does not occur. In the third stanza, the author talks
about the prerequisites of developing attachment for the Saṅkīrtana: humility
and tolerance. The author employs vyatireka alaṅkāra to embellish this stanza
by comparing humility with a grass and tolerance with a tree. In this figure
of speech, the subject of illustration (upamāna) has higher qualities than the
subject of comparison (upameya). Thus, the author says that one should be
lower than a grass and more tolerant than a tree. In the fourth stanza,
multiple things (wealth, followers, beautiful women and flowery language of
Vedas) are coupled with a single property “na kāmaye” (do not desire). This
device is called tulyayogitā alaṅkāra. In the fifth stanza, the author
beautifully couples metaphor and simile to express his eternal servitude to
Govinda. The author compares the way water drops fall from a lotus into the
mud, similarly, he has fallen from Govinda’s lotus feet to the ocean of
nescience (material existence) as a dust-like servant. The author requests
Govinda to place him back at his lotus feet. In the sixth stanza, again
tulyayogitā alaṅkāra is employed to connect different symptoms mentioned to a
single property. In the seventh stanza, the author expresses his intense
separation from Govinda by deploying three similes (upamā alaṅkāra). The
author uses these similes to express his love in the mood of separation. He
compares a moment to a great millennium, his eyes to the rainy season, and the
entire world to void. This garland of similes (mālopamā alaṅkāra) serves as an
offering to express the author’s love for Govinda. The final stanza employs
the anuktanimitta-viśeṣokti device, wherein a condition is expressed but the
consequent effect is absent, and no explanation is offered for the lack of
effect. This constitutes the anukatanimitta-viśeṣokti alaṅkāra. The author
enumerates several potential causes for being despised, yet the anticipated
outcome of animosity does not manifest. Despite hatred conditions, the author
maintains devotion to the lord. The rationale for the absence of hatred is not
mentioned here. In conclusion, the Śikṣāṣṭaka employs a range of alaṅkāras to
express its mood (rasa) without hindrance. The appropriate use of metaphors,
similes, and other figures of speech serves to create a garland-like effect
that acknowledges Govinda’s glory and expresses the author’s devotion and
love.

#### Open issues and future direction:

Moving forward, several directions for research on alaṅkāras can be explored.
One crucial area is the formulation of the problem of identifying alaṅkāras.
Since alaṅkāras can be assigned to complete or partial stanzas, or sequences
of syllables or pairs of words, determining the appropriate approach for
identifying them is non-trivial. Different formulations, such as sentence
classification, sequence labeling, or structured prediction, can be employed.
Another interesting direction for research is to investigate which alaṅkāras
are more beautiful and how we can compare two compositions based solely on
their use of alaṅkāras. Defining a basis for evaluating beauty in poetry is a
challenging problem in itself. However, understanding which alaṅkāras
contribute more to the aesthetic appeal of a poem and how to measure this
appeal can be valuable for poets and scholars alike. Finally, exploring the
correlation of alaṅkāra school with other schools of kāvyaśāstra, such as rasa
and dhvani, is a promising area for future research. Understanding how these
different aspects of poetry interact can provide insight into the complex
mechanisms of poetic expression and perception. Overall, these future
directions offer exciting opportunities to deepen our understanding of
alaṅkāras in poetry.

###  3.3 rasa school

#### Basics:

The rasa school of Indian aesthetics places significant emphasis on the
emotional impact of poetry on the reader or audience. Bharata munī, the author
of the nāṭyaśāstra, is considered the most influential thinker associated with
this school. His treatise on Indian performing arts includes a detailed
discussion of rasa theory, which posits that rasa is the soul of poetry.
According to Bharata, rasa is the ultimate emotional pleasure that can be
derived from a work of art. rasa is the heightened emotional response to the
text. Bharata also classified the various emotions depicted in performing arts
into eight different rasas, or flavors, which are śṛṅgāra (romance), hāsya
(comedy), karuṇa (piteous), raudra (anger), vīra (heroism), bhayānaka (fear),
bībhatsa (disgust), and adbhuta (wonder). The ninth emotion, śānta (peace) is
also enlisted by the other scholars.131313na yatra duḥkhaṃ na sukhaṃ na dveṣo
nāpi matsaraḥ— samaḥ sarveṣu bhūteṣu sa śāntaḥ prathito rasaḥ ——, nāṭyaśāstra
.
Where there is absence of sorrow, joy, hatred, and jealousy, with existing
sense of equality for everyone is the ‘śānta rasa’. The śānta rasa is not
compatible for dramas but other kinds of poetry can be composed in this rasa.
The concept of rasa theory remains an integral part of Indian culture and has
greatly influenced the performing arts in India and beyond.

In Bharata’s nāṭyaśāstra, a
formula141414vibhāvānubhāvavyabhicārisaṃyogādrasaniṣpattiḥ— ,nāṭyaśāstra
The rasa is the combined effect of vibhāvā, anubhāva, vyabhicāribhāva for the
arousal of rasa is presented, wherein the combination of vibhāva, anubhāva,
and vyabhicārī bhāva bhāva is necessary to evoke the experience of rasa. The
term ‘vibhāva’ refers to the stimulants of emotions, while ‘anubhāva’
represents the physical responses that accompany emotional reactions, and
‘vyabhicārī bhāva’ denotes the transitory emotions. The basic emotions or
bhāvas of the reader or spectator are activated by the vibhāvas, while the
anubhāvas and vyabhicārī bhāvas serve to indicate the emotional response
experienced. This formula suggests that the experience of rasa is not solely
dependent on a single aspect of the literary text or performance, but rather
requires the combination of multiple elements to evoke an emotional response.

#### Computational aspect:

Computational identification of rasa in poetry is an interesting and
challenging research area. One of the main challenges in identifying rasa
computationally is that the interpretation of rasa is subjective. Different
readers or critics may have different opinions on the dominant emotion evoked
by a particular work of poetry. Another challenge is the complexity of the
vibhāva, anubhāva, and vyabhicārī-bhāva that contribute to the formation of
rasa. These elements are often implicit or subtle in the text, and their
identification requires a deep understanding of the cultural and literary
context in which the text was produced. To overcome these challenges, possible
computational approaches that can be taken include using machine learning
algorithms to identify patterns in the text that are associated with
particular emotions, and incorporating contextual information such as the
author, genre, and historical period. In addition, the use of computational
linguistics techniques, such as sentiment analysis and topic modeling, may
also be helpful in identifying the dominant emotions expressed in a text.
However, it is important to note that while computational systems may be able
to identify the dominant rasa of a work of poetry, they may not be able to
fully capture the richness and complexity of the vibhāva, anubhāva, and
vyabhicārī-bhāva that contribute to the formation of rasa. The identification
of these elements requires a deep understanding of the cultural and literary
context in which the text was produced, and is likely to remain the purview of
human literary critics and scholars. In conclusion, while computational
approaches may be able to provide some insight into the identification of rasa
in poetry, the complexity and subjectivity of rasa theory poses significant
challenges. Further research in this area is needed to develop computational
models that can better capture the cultural and literary context of poetic
works and the nuances of the vibhāva, anubhāva, and vyabhicārī bhāva that
contribute to the formation of rasa.

####  Śikṣāṣṭaka analysis:

A fundamental aspect of evoking rasa involves combining three elements, namely
vibhāva, anubhāva, and vyabhicārī bhāva. The vibhāvas activate the basic
emotions or bhāvas of the reader or spectator, while the anubhāvas and
vyabhicārī bhāvas indicate the emotional response experienced. In the
composition under discussion, the author assumes the mood of a devotee and
reciprocates with his beloved Lord Kṛṣṇa. The author employs several words to
indicate that the vibhāva is kṛṣṇa, including śrī-kṛṣṇa-saṅkīrtanam
(congregational chanting of Kṛṣṇa’s holy name), nāmnām (Kṛṣṇa’s holy name),
hariḥ (another name of Kṛṣṇa), nanda-tanuja (Kṛṣṇa, the son of Nanda Maharaj),
tava nāma-grahaṇe (chanting Kṛṣṇa’s holy name), Govinda (another name of
Kṛṣṇa), and mat-prāṇa-nāthaḥ (the master of my life). The anubhāva of the
author is evident in the seventh stanza, where he expresses intense feelings
of separation. He considers even a moment to be a great millennium, and tears
flow from his eyes like torrents of rain. He perceives the entire world as
void. The author employs several words to indicate the vipralambha sṛṅgāra,
such as nānurāgaḥ (no attachment to Kṛṣṇa), a-darśanāna (Kṛṣṇa not being
visible), govinda-viraheṇa (separation from Govinda), and mat-prāṇa-nāthaḥ
(the master of my life). In conclusion, it is evident from our analysis of
vibhāva and anubhāva in this composition that the rasa evoked is vipralambha
sṛṅgāra, which is characterized by intense feelings of separation and longing.
The author effectively employs vibhāvas, such as the names and descriptions of
Kṛṣṇa, to activate the basic emotions of the reader or spectator, while his
anubhāvas, such as his intense feelings of separation and tears, serve to
indicate the emotional response experienced. The composition is a powerful
example of how the combination of vibhāva and anubhāva can be used to evoke
rasa in Indian classical literature.

#### Open issues and future direction:

The future direction of computational linguistics in identifying rasa in
poetry requires a comprehensive approach that covers all the crucial
dimensions of the problem. Data annotation is one crucial aspect of the future
direction of computational linguistics in identifying rasa in poetry. Data
annotation involves the manual tagging of texts with information such as the
dominant rasa, vibhāva, anubhāva, and vyabhicārībhāva. Possible approaches
that can be taken include using supervised machine learning algorithms to
identify patterns in the text that are associated with particular emotions.
This involves training a model on a labeled dataset of texts annotated with
the dominant rasa and associated vibhāva, anubhāva, and vyabhicārībhāva.
Another approach is to use unsupervised machine learning algorithms such as
clustering and topic modeling to identify the dominant emotions expressed in
the text. This approach requires minimal human annotation. In addition,
incorporating contextual information such as the author, genre, and historical
period can also be useful in identifying the dominant rasa in a text.

###  3.4 rīti school

#### Basics:

In this study, the focus is on the concept of rīti, also referred to as mārga
(way), in poetry. This aspect of poetry has been heavily emphasized by the
scholar Vāmana, who considers rīti as the soul of poetry. According to Vāmana,
there are three rītis, namely vaidarbhī, gauḍī, and pāñcālī, which were named
after the geographical areas from where poets constructed in these styles. The
deterministic elements of rīti include the letters, length and quantity of
compounds, and the complexity or simplicity of the composition. The vaidarbhī
style is considered the most delightful style of poetry, consisting of all ten
guṇas151515samagraguṇopetā vaidarbhī— 2.11, Kāvyālaṅkāra-sūtravṛtti
The composition style having all the qualities is vaidarbhī explained by
Vāmana. The construction of vaidarbhī contains a shorter compounds. 161616We
need to perform empirical analysis of existing annotated poetry to get
threshold of length of short compounds. The gauḍī style, dominated by oja and
kānti guṇas, 171717ojaḥkāntimatī gauḍīyā— 2.12, Kāvyālaṅkāra-sūtravṛtti
oja and kānti are the qualities (guṇas) that exist in the construction with
long compounds and complex arrangement of letters. When these qualities are
explicit in the writing style, the rīti is called as gauḍī. and lacks
sukumāratā and mādhurya guṇas. sukumāratā and mādhurya are the qualities which
occur in a construction having less compounds and soft letter combinations are
used. But, here in the gauḍī, the composition possesses long compounds and too
many joint consonants. pāñcālī style has a simple composition having no or
less compounds and simple construction.

Vāmana also describes ten qualities of sound and ten qualities of meaning,
including śleṣa (close association), prasāda (simplicity), samatā (uniformity
of diction), mādhurya (sweetness or pleasantness), sukumaratā (softness),
arthavyakti (explicitness), udārata (raciness), oja (floridity), kānti
(brilliancy), and samādhi (symmetry).181818ojaḥ
prasadaśleṣasamatāsamādhimādhuryasaukumāryodāratārthavyaktikāntayo
bandhaguṇāḥ—— 3.4, Kāvyālaṅkāra-sūtravṛtti
Śleṣa, prasāda, Samatā, mādhurya, Sukumaratā, Arthavyakti, Udārata, oja,
Kānti, and Samādhi are the 10 qualities of diction. These 10 qualities of
poetry are compressed into 3 qualities suggested by letters, compounds, and
diction. mādhurya (pleasantness), which leads to the melting of the mind, is
suggestive of the sparśa consonants (k, kh, g, gh, c, ch, j, jh, t, th, d, dh,
p, ph, b, bh) with the exception of those in the ‘ṭa’ class (ṭ, ṭh, ḍ, ḍh),
combined with nasel consonants (ṅ, ñ, n, m), the consonants ‘r’ and ‘ṇ’ when
followed by a short vowel, and when there are no or medium length compounds.
oja, the cause of lustrous expansion of mind, is suggestive of complex diction
consisting of combinations of first consonants of the class (k, c, ṭ, t, p)
with the second consonants (kh, ch, ṭh, th, ph) and the third (g, j, ḍ, d, b)
with the fourth one gh, jh, ḍh, dh, bh), any consonant with ‘r’ in any order,
any consonant with itself, the ‘ṭa’ class without ‘ṇ’, ‘ś’ and ‘ṣ’, and
consisting of long compounds. prasāda is present in all the rasas and all
kinds of poetries and rītis equally. In prasāda guṇa, words can be
comprehended right after the hearing of it. In conclusion, rīti plays an
essential role in the composition of poetry, as emphasized by Vāmana.
vaidarbhī, gauḍī, and pāñcālī are the three rītis, each having its own unique
features and characteristics. Additionally, the ten qualities of sound and ten
qualities of meaning and their compression into three guṇas suggested by
letters, compounds, and diction are important elements of rīti. The proper
deployment of these elements can significantly enhance the impact of poetry on
the reader or listener.

#### Computational aspect:

The identification of the rīti of a composition can be considered a
deterministic process. kāvyaśāstra provides various clues that enable the
classification of a rīti category. For instance, if a composition comprises of
soft syllables, no joint consonants, and a dearth of compounds or short
compounds, it is considered as vaidarbhī rīti. Conversely, if a composition
contains more joint consonants, long compounds, the usage of fricatives, and
specific combinations of joint syllables, it is considered as gauḍī rīti. The
remaining compositions, which do not fall into these two categories, are
classified as pāñcālī rīti. To the best of our knowledge, currently no
computational system exists that can determine the rīti of a composition.

####  Śikṣāṣṭaka analysis:

The Śikṣāṣṭaka is an example of a composition that embodies the mādhurya guṇa
and vaidarbhī rīti. This is apparent through the simple composition, usage of
soft consonants, limited occurrence of long compounds, and the restricted
usage of joint consonants. Moreover, the rasa of the kāvya is vipralambha
śṛṅgāra, which is aptly brought out through the use of vaidarbhī rīti and
mādhurya guṇa. The utilization of any other rīti would have led to a rasa
doṣa, highlighting the significance of choosing the appropriate rīti to convey
the intended rasa.

#### Open issues and future direction:

A natural direction for future research would be to consolidate the provided
clues and develop a rule-based computational system for the identification of
rīti in various compositions by different poets. This would enable automated
analysis and assessment of rīti in kāvya. An empirical investigation could be
carried out to explore the degree to which rīti is effective in identifying
the rasa of a kāvya. Additionally, further research could explore the
correlation of rīti school with other kāvyaśāstra schools. Vāmana, the founder
of the rīti school, maintains that different rīti can provide unique
experiences for readers. Therefore, it would be of interest to conduct a
cognitive analysis of brain signals of readers after exposing them to
compositions of different rītis. This would provide valuable insights into the
effect of rīti on the reader’s cognitive processes and emotional responses to
kāvya.

###  3.5 dhvani school

#### Basics:

The school of dhvani, a prominent school of Indian poetics, is associated with
Ānandavardhana, who authored the seminal work Dhvanyāloka, which expounds on
the theory of suggestion in poetry. Other significant figures in this school
include Abhinavagupta, Mammaṭa, etc. . According to the dhvani school,
poetry’s key elements lies in suggestion or dhvani, which alludes to the
verbal, hidden, and profound aspects of poetry. This school emphasizes the
power of suggestion and implication in poetry and argues that a poem’s true
meaning is not merely in its literal content, but in the emotional response it
elicits in the reader through suggestion and implication. The meaning is
distinguished in three categories : (1) vācya or literal meaning, (2) lakṣaṇa
or indirect meaning, which is preferred when the literal meaning is inadequate
and contradictory, and (3) vyaṅgya or poetic/metaphysical meaning, which is a
deeper meaning that does not conflict with the literal meaning and evokes
wonder by reaching out to the soul of poetry. When the  vyaṅgyārtha is felt
more delightful than the other meanings, the  vyaṅgyārtha is called as
dhvani.191919yatrārthaḥ śabdo vā tamarthamupasarjanīkṛtasvārthau — vyaṅktaḥ
kāvyaviśeṣaḥ sa dhvaniriti sūribhiḥ kathitaḥ—— 1.13, Dhvanyāloka
(When the word and its meaning in a poetry, bestow to obtain the suggestive
sense, which arouses the pleasure, is called as the dhvani by the learned
men.) Based on the degree of dhvani, a poem is classified into three
categories that demonstrate high, medium, or low conformity with the standards
of fine Sanskrit poetry, as articulated by experts in kāvyaśāstra: (1) uttama
kāvya or high composition, (2) madhyama kāvya or medium composition, and (3)
adhama kāvya or low composition. In uttama kāvya, dhvani is present, evoking
wonder in the reader. In madhyama kāvya,  vyaṅgyārtha is present, but it does
not evoke wonder compared to vācyārtha, while in adhama kāvya, dhvani is
absent. Furthermore, dhvani is divided into three broad categories: (1) vastu-
dhvani, which implies some rare fact or idea, (2) alaṅkāra-dhvani, which
suggests a figure of speech, and (3) rasa-dhvani, which evokes a feeling or
mood in the reader.

#### Computational aspect:

Identifying dhvani in kāvya computationally is a complex and challenging task
due to the subjective nature of literary interpretation and the intricacy of
the language. dhvani, which encompasses various layers of meaning, including
literal, indirect, and metaphoric, presents a challenge to computational
identification due to the absence of annotated data. Poetic devices such as
simile, metaphor, and alliteration add to the complexity of creating a unified
set of features for the identification of dhvani. Furthermore, identifying
dhvani requires additional information, such as the context, mood of the
composer, his biography, and his other compositions. The cultural and
historical context further complicates the identification of dhvani, which
often requires scholars’ commentaries to decode the layers of meanings. Even
humans may not be able to identify dhvani without these inputs, indicating the
level of expertise required for such tasks. At present, to the best of our
knowledge, no system is available to provide dhvani analysis for Sanskrit
poetry.

####  Śikṣāṣṭaka analysis:

The Śikṣāṣṭaka is a set of 8 stanzas containing sublime instructions delivered
without any specific audience. In contrast to the Bhagavad-gītā, which is
directed towards a particular audience, the Śikṣāṣṭaka is meant for inner
contemplation and self-instruction. We can draw three possible dhvanis from
these 8 stanzas. The first dhvani deals with the sambandha, abhidheya, and
prayojana for a devotee. sambandha refers to the relation of the subject with
the abhidheya of devotion, abhidheya refers to the means of devotion which is
being stated, and prayojana refers to the fruit of devotion. The first five
stanzas of the Śikṣāṣṭaka discuss the sambandha aspect, while the entire set
of stanzas serves as the abhidheya. The last three stanzas focus on prayojana,
which involves absorption in the remembrance of Kṛṣṇa and the intense emotions
that this experience brings.

The second dhvani presents the higher stages of devotional service. The first
five stanzas describe sādhana bhakti, or the devotional service that is
practiced through discipline and rules. The last 3 stanzas discuss prema, the
ultimate perfection of devotion. The third dhvani is the biography of the
author. In the initial stanza of the Śikṣāṣṭaka, the author’s proficiency in
Sanskrit grammar and poetry is conveyed by the phrase “vidyā-vadhū-jīvanam."
The Caitanya Caritamṛta (CC) further provides a detailed description of the
author’s logical expertise, wherein he is seen to skillfully refute and
reestablish his own arguments, as well as his prowess in teaching devotion to
Kṛṣṇa through grammar. Additionally, CC narrates an incident where the author
defeated the great poetry scholar Keśava Kāśmirī. The phrase “paraṁ vijayate
śrī-kṛṣṇa-saṅkīrtanam" illustrates the author’s victorious preaching of the
message of saṅkīrtanam, or congregational chanting of the holy names of Kṛṣṇa.
CC even goes on to mention how animals like tigers, deers and elephants were
inspired to participate in saṅkīrtanam, resulting in a blissful embrace
between a tiger and a deer. The second stanza of the Śikṣāṣṭaka reveals the
author’s egalitarian nature, as he considered everyone to be eligible to
participate in saṅkīrtanam without any discrimination. The third stanza
introduces the author’s bīja-mantra, which urges one to develop a taste for
saṅkīrtanam and show mercy towards all living entities. The author’s adherence
to the principle of humility is evident in his desire for devotees to follow
the same. The fourth stanza recounts the author’s renunciation of wealth,
followers, and even his beautiful wife at the age of 24 to embrace the life of
a sanyāsī, or a renunciant. The last three stanzas of the Śikṣāṣṭaka reflect
the author’s mood of separation in the last 24 years of his life. The CC
provides a vivid description of the same. In summary, the author’s teachings
in the Śikṣāṣṭaka are a reflection of his own life experiences and practices.

#### Open issues and future direction:

In future research, it is crucial to address the challenges of identifying
suggestive meaning in poetry by formulating a well-defined problem statement.
One potential direction is to explore the use of machine learning techniques
to identify dhvani in kāvya. This could involve developing annotation schemes
that capture different levels of meaning, including literal, indirect, and
metaphoric, which can be used to train machine learning models. Evaluation of
performance is another important direction for future research. Metrics could
be developed to measure the accuracy of the system’s predictions of dhvani.
These metrics could be based on human evaluations or derived automatically by
comparing the system’s output to expert annotations. One addional aspect that
could be explored in future research is the use of multi-lingual and cross-
lingual approaches for identifying dhvani. Many works of Sanskrit poetry have
been translated into other languages, and it would be interesting to
investigate whether the same dhvani can be identified across languages, and
whether insights from one language can be used to improve the identification
of dhvani in another language. Lastly, researchers could explore ways of
integrating multiple sources of information to improve the accuracy of dhvani
identification. For example, incorporating biographical information about the
composer, their other works, and the cultural and historical context of the
composition could help to disambiguate multiple possible meanings and identify
the intended dhvani.

###  3.6 vakrokti school

#### Basics:

Kuntaka’s vakrokti school is a prominent school of Indian poetics that
emphasizes the use of oblique expressions in poetry. Kuntaka’s seminal work,
Vakroktijīvita, lays out the principles of this school and classifies the
levels of expression of vakrokti into six categories. The first category is
phonetic figurativeness, which involves the skillful use of syllables to
embellish the sound of the poem. This is closely related to rītis and anuprāsa
(alliteration) alaṅkāra, which are types of śabdalaṅkāra. The second category
is Lexical figurativeness, which involves the use of oblique expressions at
the level of the root word without suffix. The third category is the
obliqueness in the suffixes. The fourth category is involves the
figurativeness, which involves the use of oblique expressions at the level of
the sentence. In this category, one has to rely on a complete sentence to
understand the oblique meaning. Different arthalaṅkāras are categoriesed under
this category. The fifth category is sectional figurativeness, which involves
the twist in the chapter-wise arrangement of the poetry. The sixth category is
compositional figurativeness, which involves understanding the oblique meaning
by relying on the complete composition. Kuntaka considers vakrokti to be the
soul of poetry, and argues that it is the only embellishment possible to the
word and its meaning. The use of vakrokti is essential to create effective
poetry, and mastery of the six levels of expression is fundamental to the
creation of effective poetry in the vakrokti school.

#### Computational aspect:

Upon analysis of Kuntaka’s vakrokti school, it becomes apparent that his
theory of oblique expression incorporates various elements of the previously
established schools of rīti, rasa, dhvani, and alaṅkāra. Despite this,
Kuntaka’s contribution to the field lies in his systematic classification of 6
levels of oblique expression. However, the computational challenges posed by
the deep semantics of this theory are similar to those discussed in the other
schools. Therefore, it is difficult to develop a module capable of accurately
identifying vakrokti in a composition. To date, no computational system exists
for computing vakrokti, as it remains a complex task.

####  Śikṣāṣṭaka analysis:

The present analysis examines the use of oblique expressions in Śikṣāṣṭaka.
The study identifies all 6 categories of oblique expressions deployed in the
poem. The first category, phonetic figurativeness, concerns the skillful use
of syllables to enhance the poetic sound, and we find that Śikṣāṣṭaka employs
various types of anuprāsa alaṅkāras. The second category, word-root level
figurativeness, relates to the use of oblique expressions at the level of
individual words, and the poem utilizes rūpak alaṅkāra for this purpose. The
third category, sentential figurativeness, focuses on oblique expressions at
the level of sentences, and employs several arthalaṅkāras. The fourth
category, Contextual Figurativeness, relies on the poem’s context and utilizes
a series of rūpaka alaṅkāras to create a garland-like effect. The fifth
category, compositional figurativeness, involves understanding the oblique
meaning by examining the poem’s different section. Śikṣāṣṭaka uses this
category to discuss stages of bhakti and the concept of sambandha, abhidheya,
and prayojana in an oblique manner. The final category, refers to the use of
complete composition to convey oblique. We find that the author talks about
his biography in the entire composition in an oblique manner. Overall, the
study reveals that Śikṣāṣṭaka employs all six categories of oblique
expressions, highlighting the author’s mastery of poetic devices and his
ability to convey complex spiritual ideas in a highly nuanced and layered
manner.

#### Open issues and future direction:

As the field of NLP advances, there is growing interest in exploring the use
of oblique expressions in computational models. In particular, the study of
oblique expressions can contribute to the development of natural language
generation, sentiment analysis, and machine translation systems. One potential
area of research is the identification and classification of oblique
expressions in large corpora of texts. Machine learning algorithms can be
trained to recognize patterns of oblique expression usage and distinguish
between different types of oblique expressions, such as the six categories
identified in the present analysis of Śikṣāṣṭaka. This would require the
creation of annotated datasets that can be used for training and testing
purposes. Another area of research is the development of computational models
that can generate oblique expressions in natural language. Such models could
be trained to generate oblique expressions based on the context of the text
and the intended meaning. This would require a deep understanding of the
different types of oblique expressions and their functions, as well as the
ability to generate language that is both grammatically correct and
semantically appropriate. Despite the potential benefits of using oblique
expressions in computational models, there are also several challenges that
need to be addressed. One of the main challenges is the ambiguity of oblique
expressions, which can make it difficult for computational models to
accurately interpret their meaning. Another challenge is the variability of
oblique expression usage across different languages and cultural contexts,
which requires a more nuanced and context-specific approach.

###  3.7 aucitya school

#### Basics:

Kṣemendra, a renowned poet of the 11th century, introduced the concept of
aucitya in his seminal work aucitya-vicāra-carcā. aucitya, meaning
appropriateness, suggests that the elements of poetry, such as rasa, alaṅkāra,
and rīti, should be used in an appropriate
manner.202020ucitasthānavinyāsādalaṅkṛtiralaṅkṛtiḥ — aucityādacyutā nityaṃ
bhavantyeva guṇā guṇāḥ——
(The figures are decorative when they do not overpass the appropriateness in
the poetry. The qualities can be assumed as qualities in real sense when they
follow the validity of appropriteness.) 1.6, aucitya-vicāra-carcā aucitya is
considered the soul of a poem, and appropriateness is regarded as the secret
of beautiful composition. This theory has been widely accepted by scholars
without any argument and is often referred to as the ‘Theory of Coordination’
since it regulates all aspects of nāṭyaśāstra. aucitya is a tool that aids
writers in wielding their poem according to their will and effectively
delivering their ideas. Kṣemendra categorized aucitya into several classes,
namely pada (word form), vākya (sentence), prabandhanārtha (meaning of the
whole composition), guṇa(qualities), alaṅkāra (poetic figures), rasa
(sentiments), etc. In conclusion, Kṣemendra’s concept of aucitya has had a
significant impact on the field of poetry. The idea of appropriateness and the
use of poetry elements in a balanced manner are essential components of
successful composition. The categorization of aucitya into multiple classes
provides a comprehensive framework for analyzing and understanding the nature
of poetry. Therefore, aucitya is an invaluable tool for writers, enabling them
to deliver their ideas efficiently.

#### Computational aspect:

According to the available literature, no computational system currently
exists that provides an analysis of aucitya. In order to develop a module for
aucitya analysis, we propose considering the mutual compatibility of rīti,
rasa, and alaṅkāra in the initial implementation. For instance, vaidarbhī is
considered a compatible rīti when deploying the sṛṅgāra rasa, while gauḍī is
appropriate for the vīra rasa. Additionally, certain alaṅkāras are suitable
for specific rasas. At a later stage, we may annotate corpora and build data-
driven metrics to automatically measure the aucitya of a composition. However,
to accomplish this, it is essential to establish standardized data annotation
policies in advance. One major challenge in evaluating poetic appropriateness
across various languages, cultures, and time periods is the lack of
standardized rules or models. Furthermore, the subjective nature of poetic
appropriateness makes it challenging to reach a consensus among scholars and
experts on the definition of aucitya.

####  Śikṣāṣṭaka analysis:

Our analysis suggests that the Śikṣāṣṭaka is an exemplary composition that
demonstrates aucitya. The composition employs the vipralambha sṛṅgāra rasa,
and the vaidarbhī rīti with the mādhurya guṇa, which are perfectly compatible.
Additionally, the use of alaṅkāras is deployed in an appropriate manner,
without overwhelming the expression of the rasa. The composition’s rasa
remains consistent and does not change abruptly. Instead, it gradually
intensifies throughout the composition, reaching its pinnacle in the last
stanza. This uniformity in the rasa’s expression contributes to the
effectiveness of the composition in evoking the desired emotional response.

#### Open issues and future direction:

Moving forward, the development of a computational system for aucitya analysis
presents an exciting area of research. In terms of future directions, several
questions can be explored. Firstly, the effectiveness of the proposed mutual
compatibility approach between rīti, rasa, and alaṅkāra needs to be evaluated
by analyzing the performance of the initial module. Furthermore, additional
features could be incorporated to improve the accuracy of aucitya analysis,
such as word choice, meter, and rhyme patterns. Moreover, there is a need to
establish standardized guidelines for the annotation of corpora in different
languages and cultural contexts. This would facilitate the creation of a
large, diverse dataset that can be used to train the aucitya analysis system.
Additionally, research could focus on the development of data-driven metrics
that automatically evaluate poetic appropriateness. Another potential
direction for research is to investigate the interplay between language,
culture, and poetic appropriateness. This involves analyzing the extent to
which poetic conventions vary across different languages and cultures and how
these variations affect the evaluation of aucitya. The impact of historical
and temporal changes on poetic conventions can also be explored to understand
the evolution of poetic conventions over time. Finally, collaboration between
experts in literature and computer science can help establish a consensus on
what constitutes aucitya. This could lead to the development of a standardized
set of rules and models for evaluating poetic appropriateness, which could be
applied across different languages, cultures, and time.

##  4 The proposed framework

Figure 1: The proposed framework for analysis and classification of poetry
using a hierarchical ensembling architecture. It consists of 7 modules, with
violet modules being deterministic and the rest being supervised modules,
currently supported by human experts. All modules are trained independently.
The outputs and features of previous modules are helpful for the next phase
modules, and the aucitya module learns the weight of each module using all
their outputs except the meter module. The composition is finally classified
into three classes that demonstrate high, medium, or low conformity with the
standards of fine Sanskrit poetry, as articulated by experts in kāvyaśāstra.
We illustrate the proposed framework by showing analysis on Śikṣāṣṭaka
composition.

This section presents the description of a proposed framework for the analysis
and classification of poetry. The framework is designed to categorize
compositions into 3 classes that demonstrate high, medium, or low conformity
with the standards of fine Sanskrit poetry, as articulated by experts in
kāvyaśāstra. Figure 1 depicts the proposed framework, which employs a
hierarchical ensembling architecture consisting of 7 modules. The violet
modules are deterministic, while the remaining modules are learning-based and
currently supported by human experts. Each module can be trained
independently, and the outputs and features of the previous modules are
utilized to enhance the performance of the next phase modules. The aucitya
module is responsible for learning the weight of each module by employing all
their outputs, except the meter module. We illustrate the proposed framework
by showing analysis on Śikṣāṣṭaka composition.

The first layer of the framework consists of 3 modules namely, rīti, Meter and
alaṅkāra module. The rīti module is the first module in the proposed
framework, and it is responsible for identifying the rīti of a composition.
This is deterministic, and the classification is enabled by various clues
provided by the kāvyaśāstra. The next module, the meter identification module,
is also deterministic, and commendable efforts have been made by the SCL
community in recent years to develop user-friendly toolkits for the
identification of meter Neill (2023); Rajagopalan (2018); Terdalkar and
Bhattacharya (2023). In the alaṅkāra module, the identification of
śabdalaṅkāra is considered deterministic, and it involves verifying the
occurrence of specific patterns of syllables or words. In contrast, the
identification of arthalaṅkāra presents a significant semantic challenge, even
for experienced annotators. The module relies on a supervised paradigm of
binary classification to identify whether any arthalaṅkāra is present or not.
The rasa and vakrokti (oblique) modules are the next two modules in the
framework. For the rasa module, a classification problem with 9 classes of
rasas is framed. These rasas are śṛṅgāra (love and beauty), hāsya (comedy),
karuṇa (piteous), raudra (anger), vīra (heroism), bhayānaka (fear), bībhatsa
(disgust), adbhuta (wonder), and śānta (peace). It is argued that rīti and
meter may be helpful and can serve as auxiliary information to identify rasa;
therefore, they are used as features in the rasa module. The vakrokti module
is framed as a binary classification problem to identify the presence of
oblique. Here, the alaṅkāra module has a strong correlation in contributing to
oblique identification. The next layer of the module is the dhvani module,
which is also a classification problem with 3 classes: direct meaning,
indirect meaning, and suggestive meaning. Suggestive meaning has a strong
correlation with rasa, alaṅkāra, and vakrokti. Therefore, these features are
plugged into the dhvani module. Finally, the aucitya module learns the weight
of each module using a supervised paradigm. These weighted features of all
modules are used for the final classification of the composition into three
classes that demonstrate high, medium, or low conformity with the standards of
fine Sanskrit poetry, as articulated by experts in kāvyaśāstra. In the absence
of annotated data, human experts are relied upon for the modules that are
supervised modules. In the future, it is hoped that all the modules can be
automated, and researchers can consider training these modules in an end-to-
end fashion. Overall, the proposed framework presents a systematic approach to
analyze and classify poetry into different categories based on various
features. The framework has the potential to assist poets, scholars, and
critics in the evaluation of compositions and provide insights into the
nuances of poetry.

Figure 2: Web-based interactive modules to illustrate annotations and poetry
analysis. Here, we showcase the verse-level analysis for alaṅkāra module.

#### Is Śikṣāṣṭaka an uttama kāvya?

The criterion for a composition to be qualified as an uttama kāvya is the
presence of dhvani, which evokes wonder in the
reader.212121idamuttamamatiśayini vyaṅgace vācyād dhvanirbudhaiḥ kathitaḥ—1.4,
Kāvyaprakāśa
The highest kind of poetry is the one in which the suggestive meaning
dominates the other meanings. In this case, the suggestive meaning is called
dhvani by scholars. dhvani is the soul of a kāvya and is of three types:
vastu-dhvani, alaṅkāra-dhvani, and rasa-dhvani. Vastu-dhvani signifies rare
facts or ideas; alaṅkāra-dhvani indicates figures of speech, and rasa-dhvani
evokes feelings or moods in the reader. In the context of vastu-dhvani,
Śikṣāṣṭaka explores the sambandha, abhidheya, and prayojana for a devotee,
gradations of devotional service, and the biography of the author. The
composition provides an insightful glimpse into the key elements of bhakti and
its various stages, making it a source of rare knowledge for the reader. In
terms of alaṅkāra-dhvani, Śikṣāṣṭaka employs a range of figures of speech such
as metaphors, similes, and other literary devices to express its mood (rasa)
without hindrance. The appropriate use of these devices creates a garland-like
effect that acknowledges Govinda’s glory and expresses the author’s devotion
and love. The composition’s poetic beauty is further enhanced by its rhythm
and musicality, making it a delight for readers. Moreover, Śikṣāṣṭaka is a
powerful example of how the combination of vibhāva and anubhāva can be used to
evoke vipralambha sṛṅgāra rasa, making it an exemplar of rasa-dhvani. The
composition conveys the feeling of separation from the divine, which is
central to the Vaiṣṇava tradition of bhakti, and generates a deep emotional
response in the reader. In conclusion, the evidence presented above
establishes that Śikṣāṣṭaka is indeed an uttama kāvya. Its exploration of rare
knowledge, its alaṅkāra beauty, and its evocation of deep emotions through
rasa-dhvani which renders greater amusement than the other meanings make it a
masterpiece of Sanskrit literature.

##  5 Web Interface

This work employs compound tagging, morphological tagging, Kāraka dependency
tagging, and anvaya to annotate the Śikṣāṣṭaka. The primary objective of this
annotation exercise is to facilitate a literal understanding of the
composition. By providing grammatical information, this annotation serves as a
baseline to evaluate the dhvani, or poetic suggestion, of the composition. The
stanzas were annotated by 4 annotators, each an expert in one of the
aforementioned tasks. In cases where there was a discrepancy in the annotation
process, the annotators discussed and resolved the issue. All annotators hold
a minimum academic qualification of a Master in Arts in Sanskrit. The
annotations are publicly available via an interactive web-based platform as
well as standard text annotation format.

#### Web-based application

Figure 2 shows our web application that offers an interactive module to
illustrate annotations and poetry analysis. The motivation to build a web-
based application to illustrate poetry analysis Delmonte (2015); Delmonte and
Prati (2014) is that it can help to make poetry analysis more accessible,
engaging, and effective, providing students with a rich learning experience
that encourages deeper understanding and appreciation of this art form. This
template can serve as a proxy to illustrate how an automated system should
produce the poetry analysis. There are 7 dimensions to our analysis which can
be classified into two broad categories, namely, stanza-level (metrical and
alaṅkāra analysis) and global-level (rīti, vakrokti, rasa, dhvani and aucitya
analysis). As the names suggest, stanza-level analysis shows the analysis for
each stanza and global analysis considers complete composition to provide the
respective analysis. The stanza-level modules are shown in blue color and the
rest in purple. Our platform can provide the analysis in two possible ways.
First, a user can choose to analyze any stanza through all the modules.
Otherwise, the user can also opt for choosing any module and analyzing all the
stanzas from the perspective of the chosen module. Our web template leverages
the flex module to provide interactive features.

##  6 Conclusion

In conclusion, this article presents an innovative approach to bridge the gap
between Sanskrit poetry and computational linguistics by proposing a framework
that classifies Sanskrit poetry into levels of the characteristics of fine
composition. The proposed framework takes a human-in-the-loop approach,
combining the deterministic aspects delegated to machines and the deep
semantics left to human experts. The article provides a deep analysis of
Śikṣāṣṭaka, a Sanskrit poem, from the perspective of 7 prominent kāvyaśāstra
schools to illustrate the proposed framework. The analysis establishes that
Śikṣāṣṭaka is indeed the uttama kāvya composition. Moreover, the article
provides compound, dependency, anvaya, meter, rasa, alaṅkāra, and rīti
annotations for Śikṣāṣṭaka and a web application to illustrate the poem’s
analysis and annotations. The roadmap of the proposed framework opens new
possibilities for the automatic analysis and classification of Sanskrit poetry
while preserving the rich tradition of Sanskrit poetry.

## Ethics Statement

Our work proposes a roadmap framework to evaluate the aesthetic beauty of
Sanskrit poetry, which we believe will be valuable to individuals interested
in the analysis of Sanskrit poetry. We have taken great care to ensure that
our analysis is conducted ethically and responsibly. We do not anticipate any
adverse effects of our framework and analysis on any community.

## Acknowledgement

We would like to express gratitude to several individuals who contributed to
the successful completion of this research project. We are grateful to
Chaitanya Lakkundi for his helpful discussions on grammar. We would like to
extend appreciation to Dr. Anupama Rayali, Dr. Pavankumar Salutari and Dr.
Saurabh Dwivedi (Buddh P G College, Kushinagar, Uttar Pradesh) for their
assistance in annotating Śikṣāṣṭaka. We are also thankful to Sugyan Kumar
Mahanty for providing valuable inputs in their metrical analysis. We thank
Hrishikesh Terdalkar for helping us with the metrical analysis and web
designing. We acknowledge the support and assistance of Gauranga Darshan
Prabhu, Dr. Amba Kulkarni (University of Hyderabad), Leela Govind Prabhu,
Sriram Krishnan, Vedantasutra Prabhu and Venu Gopal Prabhu in connecting with
different scholars of poetry school. We are also grateful to Shatavadhani R.
Ganesh for his insightful discussions on clarifying our doubts. We appreciate
the anonymous reviewers for their insightful suggestions that helped in
enhancing this work. The work of the first author is supported by the TCS
Fellowship under Project TCS/EE/2011191P.

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##  Appendix A Śikṣāṣṭaka Composition

Stanza 1

ceto-darpaṇa-mārjanaṁ bhava-mahā-dāvāgni-nirvāpaṇaṁ |

śreyaḥ-kairava-candrikā-vitaraṇaṁ vidyā-vadhū-jīvanam ||

ānandāmbudhi-vardhanaṁ prati-padaṁ pūrṇāmṛtāsvādanaṁ |

sarvātma-snapanaṁ paraṁ vijayate śrī-kṛṣṇa-saṅkīrtanam ||1||

Synonyms: cetaḥ — of the heart; darpaṇa — the mirror; mārjanam — cleansing;
bhava — of material existence; mahā-dāva-agni — the blazing forest fire;
nirvāpaṇam — extinguishing; śreyaḥ — of good fortune; kairava — the white
lotus; candrikā — the moonshine; vitaraṇam — spreading; vidyā — of all
education; vadhū — wife; jīvanam — the life; ānanda — of bliss; ambudhi — the
ocean; vardhanam — increasing; prati-padam — at every step; pūrṇa-amṛta — of
the full nectar; āsvādanam — giving a taste; sarva — for everyone; ātma-
snapanam — bathing of the self; param — transcendental; vijayate — let there
be victory; śrī-kṛṣṇa-saṅkīrtanam — for the congregational chanting of the
holy name of Kṛṣṇa.
Translation: Let there be all victory for the chanting of the holy name of
Lord Kṛṣṇa, which can cleanse the mirror of the heart and stop the miseries of
the blazing fire of material existence. That chanting is the waxing moon that
spreads the white lotus of good fortune for all living entities. It is the
life and soul of all education. The chanting of the holy name of Kṛṣṇa expands
the blissful ocean of transcendental life. It gives a cooling effect to
everyone and enables one to taste full nectar at every step.

Stanza 2

nāmnām akāri bahudhā nija-sarva-śaktis |

tatrārpitā niyamitaḥ smaraṇe na kālaḥ ||

etādṛśī tava kṛpā bhagavan mamāpi |

dur-daivam īdṛśam ihājani nānurāgaḥ ||2||

Synonyms: nāmnām — of the holy names of the Lord; akāri — manifested; bahudhā
— various kinds; nija-sarva-śaktiḥ — all kinds of personal potencies; tatra —
in that; arpitā — bestowed; niyamitaḥ — restricted; smaraṇe — in remembering;
na — not; kālaḥ — consideration of time; etādṛśī — so much; tava — Your; kṛpā
— mercy; bhagavan — O Lord; mama — My; api — although; durdaivam — misfortune;
īdṛśam — such; iha — in this (the holy name); ajani — was born; na — not;
anurāgaḥ — attachment.
Translation: My Lord, O Supreme Personality of Godhead, in Your holy name
there is all good fortune for the living entity, and therefore You have many
names, such as “Kṛṣṇa” and “Govinda,” by which You expand Yourself. You have
invested all Your potencies in those names, and there are no hard and fast
rules for remembering them. My dear Lord, although You bestow such mercy upon
the fallen, conditioned souls by liberally teaching Your holy names, I am so
unfortunate that I commit offenses while chanting the holy name, and therefore
I do not achieve attachment for chanting.

Stanza 3

tṛṇād api su-nīcena |

taror iva sahiṣṇunā ||

amāninā māna-dena |

kīrtanīyaḥ sadā hariḥ ||3||

Synonyms: tṛṇāt api — than downtrodden grass; su-nīcena — being lower; taroḥ —
than a tree; iva — like; sahiṣṇunā — with tolerance; amāninā — without being
puffed up by false pride; māna-dena — giving respect to all; kīrtanīyaḥ — to
be chanted; sadā — always; hariḥ — the holy name of the Lord.
Translation One who thinks himself lower than the grass, who is more tolerant
than a tree, and who does not expect personal honor but is always prepared to
give all respect to others can very easily always chant the holy name of the
Lord.

Stanza 4

na dhanaṁ na janaṁ na sundarīṁ |

kavitāṁ vā jagad-īśa kāmaye ||

mama janmani-janmani īśvare |

bhavatād bhaktir a-haitukī tvayi ||4||

Synonyms: na — not; dhanam — riches; na — not; janam — followers; na — not;
sundarīm — a very beautiful woman; kavitām — fruitive activities described in
flowery language; vā — or; jagat-īśa — O Lord of the universe; kāmaye — I
desire; mama — My; janmani — in birth; janmani — after birth; īśvare — unto
the Supreme Personality of Godhead; bhavatāt — let there be; bhaktiḥ —
devotional service; ahaitukī — with no motives; tvayi — unto You.
Translation: O Lord of the universe, I do not desire material wealth,
materialistic followers, a beautiful wife or fruitive activities described in
flowery language. All I want, life after life, is unmotivated devotional
service to You.

Stanza 5

ayi nanda-tanuja kiṅ-karaṁ |

patitaṁ māṁ viṣame bhava-ambudhau ||

kṛpayā tava pāda-paṅkaja- |

sthita-dhūlī-sadṛśaṁ vicintaya||5||

Synonyms: ayi — O My Lord; nanda-tanuja — the son of Nanda Mahārāja, Kṛṣṇa;
kiṅkaram — the servant; patitam — fallen; mām — Me; viṣame — horrible; bhava-
ambudhau — in the ocean of nescience; kṛpayā — by causeless mercy; tava —
Your; pāda-paṅkaja — lotus feet; sthita — situated at; dhūlī-sadṛśam — like a
particle of dust; vicintaya — kindly consider.
Translation: O My Lord, O Kṛṣṇa, son of Mahārāja Nanda, I am Your eternal
servant, but because of My own fruitive acts I have fallen into this horrible
ocean of nescience. Now please be causelessly merciful to Me. Consider Me a
particle of dust at Your lotus feet.

Stanza 6

nayanaṁ galad-aśru-dhārayā |

vadanaṁ gadgada-ruddhayā girā ||

pulakair nicitaṁ vapuḥ kadā |

tava nāma-grahaṇe bhaviṣyati||6||

Synonyms: nayanam — the eyes; galat-aśru-dhārayā — by streams of tears running
down; vadanam — mouth; gadgada — faltering; ruddhayā — choked up; girā — with
words; pulakaiḥ — with erection of the hairs due to transcendental happiness;
nicitam — covered; vapuḥ — the body; kadā — when; tava — Your; nāma-grahaṇe —
in chanting the name; bhaviṣyati — will be.
Translation: My dear Lord, when will My eyes be beautified by filling with
tears that constantly glide down as I chant Your holy name? When will My voice
falter and all the hairs on My body stand erect in transcendental happiness as
I chant Your holy name?

Stanza 7

yugāyitaṁ nimeṣeṇa |

cakṣuṣā prāvṛṣāyitam ||

śūnyāyitaṁ jagat sarvaṁ |

govinda-viraheṇa me ||7||

Synonyms 7: yugāyitam — appearing like a great millennium; nimeṣeṇa — by a
moment; cakṣuṣā — from the eyes; prāvṛṣāyitam — tears falling like torrents of
rain; śūnyāyitam — appearing void; jagat — the world; sarvam — all; govinda —
from Lord Govinda, Kṛṣṇa; viraheṇa me — by My separation.
Translation: My Lord Govinda, because of separation from You, I consider even
a moment a great millennium. Tears flow from My eyes like torrents of rain,
and I see the entire world as void.

Stanza 8

āśliṣya vā pāda-ratāṁ pinaṣṭu mām |

a-darśanān marma-hatāṁ karotu vā ||

yathā tathā vā vidadhātu lampaṭo |

mat-prāṇa-nāthas tu sa eva nāparaḥ ||8||

Synonyms: āśliṣya — embracing with great pleasure; vā — or; pāda-ratām — who
have fallen at the lotus feet; pinaṣṭu — let Him trample; mām — Me; adarśanāt
— by not being visible; marma-hatām — brokenhearted; karotu — let Him make; vā
— or; yathā — as (He likes); tathā — so; vā — or; vidadhātu — let Him do;
lampaṭaḥ — a debauchee, who mixes with other women; mat-prāṇa-nāthaḥ — the
Lord of My life; tu — but; saḥ — He; eva — only; na aparaḥ — not anyone else.
Translation: Let Kṛṣṇa tightly embrace this maidservant who has fallen at His
lotus feet, or let Him trample Me or break My heart by never being visible to
Me. He is a debauchee, after all, and can do whatever He likes, but still He
alone, and no one else, is the worshipable Lord of My heart.