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Found 23 papers, 10 papers with code
A Graph-Based Framework for Structured Prediction Tasks in Sanskrit
Ours is a search-based structured prediction framework, which expects a graph as input, where relevant linguistic information is encoded in the nodes, and the edges are then used to indicate the association between these nodes.
Does Meta-learning Help mBERT for Few-shot Question Generation in a Cross-lingual Transfer Setting for Indic Languages?
Further, we apply the model agnostic meta-learning approach to our base model.
Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit
We propose a graph-based model for joint morphological parsing and dependency parsing in Sanskrit.
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery
Further, the intent classification may be modeled in a multiclass (MC) or multilabel (ML) setup.
Adversarial Clean Label Backdoor Attacks and Defenses on Text Classification Systems
Clean-label (CL) attack is a form of data poisoning attack where an adversary modifies only the textual input of the training data, without requiring access to the labeling function.
Sāmayik: A Benchmark and Dataset for English-Sanskrit Translation
Translation models trained on our dataset demonstrate statistically significant improvements when translating out-of-domain contemporary corpora, outperforming models trained on older classical-era poetry datasets.
A Benchmark and Dataset for Post-OCR text correction in Sanskrit
Keeping this in mind, we release a multi-domain dataset, from areas as diverse as astronomy, medicine and mathematics, with some of them as old as 18 centuries.
ProoFVer: Natural Logic Theorem Proving for Fact Verification
Fact verification systems typically rely on neural network classifiers for veracity prediction which lack explainability.
Ranked #1 on
Fact Verification
on FEVER
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights
In this work, we propose the first large scale study of automatic speech recognition (ASR) in Sanskrit, with an emphasis on the impact of unit selection in Sanskrit ASR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages
In this work, we focus on dependency parsing for morphological rich languages (MRLs) in a low-resource setting.
Evaluating Neural Morphological Taggers for Sanskrit
Neural sequence labelling approaches have achieved state of the art results in morphological tagging.
SHR++: An Interface for Morpho-syntactic Annotation of Sanskrit Corpora
It incorporates analyses and predictions from various tools designed for processing texts in Sanskrit, and utilise them to ease the cognitive load of the human annotators.
Neural Approaches for Data Driven Dependency Parsing in Sanskrit
We compare the performance of each of the models in a low-resource setting, with 1, 500 sentences for training.
Poetry to Prose Conversion in Sanskrit as a Linearisation Task: A Case for Low-Resource Languages
Owing to the resource constraints, we formulate this task as a word ordering (linearisation) task.
Upcycle Your OCR: Reusing OCRs for Post-OCR Text Correction in Romanised Sanskrit
We propose a post-OCR text correction approach for digitising texts in Romanised Sanskrit.
Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit
The configurational information in sentences of a free word order language such as Sanskrit is of limited use.
Building a Word Segmenter for Sanskrit Overnight
There is an abundance of digitised texts available in Sanskrit.
A Graph Based Semi-Supervised Approach for Analysis of Derivational Nouns in Sanskrit
Derivational nouns are widely used in Sanskrit corpora and represent an important cornerstone of productivity in the language.
A Dataset for Sanskrit Word Segmentation
The last decade saw a surge in digitisation efforts for ancient manuscripts in Sanskrit.
Compound Type Identification in Sanskrit: What Roles do the Corpus and Grammar Play?
We construct an elaborate features space for our system by combining conditional rules from the grammar \textit{Adṣṭ{\=a}dhy{\=a}y{\=\i}}, semantic relations between the compound components from a lexical database \textit{Amarakoṣa} and linguistic structures from the data using Adaptor Grammars.
Word Segmentation in Sanskrit Using Path Constrained Random Walks
In Sanskrit, the phonemes at the word boundaries undergo changes to form new phonemes through a process called as sandhi.
Towards automating the generation of derivative nouns in Sanskrit by simulating Panini
We also present cases where we have checked the applicability of the system with the rules which are not specifically applicable to derivation of derivative nouns, in order to see the effectiveness of the proposed schema as a generic system for modeling Astadhyayi.
