14 citations · 28 across the 6 of their papers we have counts for
7 papers
Textless Speech-to-Speech Translation With Limited Parallel Data
Anuj Diwan, Anirudh Srinivasan, David Harwath +1
Existing speech-to-speech translation (S2ST) models fall into two camps: they either leverage text as an intermediate step or require hundreds of hours of parallel speech data. Bot…
TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages
Anirudh Srinivasan, Eunsol Choi
We study politeness phenomena in nine typologically diverse languages. Politeness is an important facet of communication and is sometimes argued to be cultural-specific, yet existi…
CALCS 2021 Shared Task: Machine Translation for Code-Switched Data
Shuguang Chen, Gustavo Aguilar, Anirudh Srinivasan +2
To date, efforts in the code-switching literature have focused for the most part on language identification, POS, NER, and syntactic parsing. In this paper, we address machine tran…
Predicting the Performance of Multilingual NLP Models
Anirudh Srinivasan, Sunayana Sitaram, Tanuja Ganu +3
Recent advancements in NLP have given us models like mBERT and XLMR that can serve over 100 languages. The languages that these models are evaluated on, however, are very few in nu…
GLUECoS : An Evaluation Benchmark for Code-Switched NLP
Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan +2
Code-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpo…
Unsung Challenges of Building and Deploying Language Technologies for Low Resource Language Communities
Pratik Joshi, Christain Barnes, Sebastin Santy +7
In this paper, we examine and analyze the challenges associated with developing and introducing language technologies to low-resource language communities. While doing so, we bring…
Automated curriculum generation for Policy Gradients from Demonstrations
Anirudh Srinivasan, Dzmitry Bahdanau, Maxime Chevalier-Boisvert +1
In this paper, we present a technique that improves the process of training an agent (using RL) for instruction following. We develop a training curriculum that uses a nominal numb…