77 citations · 157 across the 16 of their papers we have counts for
16 papers
PwR: Exploring the Role of Representations in Conversational Programming
Pradyumna YM, Vinod Ganesan, Dinesh Kumar Arumugam +7
Large Language Models (LLMs) have revolutionized programming and software engineering. AI programming assistants such as GitHub Copilot X enable conversational programming, narrowi…
Svarah: Evaluating English ASR Systems on Indian Accents
Tahir Javed, Sakshi Joshi, Vignesh Nagarajan +6
India is the second largest English-speaking country in the world with a speaker base of roughly 130 million. Thus, it is imperative that automatic speech recognition (ASR) systems…
Large Language Models Humanize Technology
Pratyush Kumar
Large Language Models (LLMs) have made rapid progress in recent months and weeks, garnering significant public attention. This has sparked concerns about aligning these models with…
IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages
Jay Gala, Pranjal A. Chitale, Raghavan AK +11
India has a rich linguistic landscape with languages from 4 major language families spoken by over a billion people. 22 of these languages are listed in the Constitution of India (…
Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR
Kaushal Santosh Bhogale, Sai Sundaresan, Abhigyan Raman +3
Improving ASR systems is necessary to make new LLM-based use-cases accessible to people across the globe. In this paper, we focus on Indian languages, and make the case that divers…
An Empirical Study of Leveraging Knowledge Distillation for Compressing Multilingual Neural Machine Translation Models
Varun Gumma, Raj Dabre, Pratyush Kumar
Knowledge distillation (KD) is a well-known method for compressing neural models. However, works focusing on distilling knowledge from large multilingual neural machine translation…
IndicMT Eval: A Dataset to Meta-Evaluate Machine Translation metrics for Indian Languages
Ananya B. Sai, Vignesh Nagarajan, Tanay Dixit +4
The rapid growth of machine translation (MT) systems has necessitated comprehensive studies to meta-evaluate evaluation metrics being used, which enables a better selection of metr…
Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages
Arnav Mhaske, Harshit Kedia, Sumanth Doddapaneni +4
We present, Naamapadam, the largest publicly available Named Entity Recognition (NER) dataset for the 11 major Indian languages from two language families. The dataset contains mor…
Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages
Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh +4
Building Natural Language Understanding (NLU) capabilities for Indic languages, which have a collective speaker base of more than one billion speakers is absolutely crucial. In thi…
Towards Building Text-To-Speech Systems for the Next Billion Users
Gokul Karthik Kumar, Praveen S, Pratyush Kumar +2
Deep learning based text-to-speech (TTS) systems have been evolving rapidly with advances in model architectures, training methodologies, and generalization across speakers and lan…
Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages
Kaushal Santosh Bhogale, Abhigyan Raman, Tahir Javed +4
End-to-end (E2E) models have become the default choice for state-of-the-art speech recognition systems. Such models are trained on large amounts of labelled data, which are often n…
IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languages
Tahir Javed, Kaushal Santosh Bhogale, Abhigyan Raman +3
A cornerstone in AI research has been the creation and adoption of standardized training and test datasets to earmark the progress of state-of-the-art models. A particularly succes…
Input-specific Attention Subnetworks for Adversarial Detection
Emil Biju, Anirudh Sriram, Pratyush Kumar +1
Self-attention heads are characteristic of Transformer models and have been well studied for interpretability and pruning. In this work, we demonstrate an altogether different util…
IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages
Aman Kumar, Himani Shrotriya, Prachi Sahu +6
Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages. In this paper, we present the IndicNLG Benchmark, a collecti…
IndicBART: A Pre-trained Model for Indic Natural Language Generation
Raj Dabre, Himani Shrotriya, Anoop Kunchukuttan +3
In this paper, we study pre-trained sequence-to-sequence models for a group of related languages, with a focus on Indic languages. We present IndicBART, a multilingual, sequence-to…
VeRLPy: Python Library for Verification of Digital Designs with Reinforcement Learning
Aebel Joe Shibu, Sadhana S, Shilpa N +1
Digital hardware is verified by comparing its behavior against a reference model on a range of randomly generated input signals. The random generation of the inputs hopes to achiev…