activity
20182022
most citedMLS: A Large-Scale Multilingual Dataset for Speech Research

354 citations · 364 across the 5 of their papers we have counts for

collaborators

10 papers

cs.LG2022

Star Temporal Classification: Sequence Classification with Partially Labeled Data

Vineel Pratap, Awni Hannun, Gabriel Synnaeve +1

We develop an algorithm which can learn from partially labeled and unsegmented sequential data. Most sequential loss functions, such as Connectionist Temporal Classification (CTC),…

eess.AS2021

Word Order Does Not Matter For Speech Recognition

Vineel Pratap, Qiantong Xu, Tatiana Likhomanenko +2

In this paper, we study training of automatic speech recognition system in a weakly supervised setting where the order of words in transcript labels of the audio training data is n…

cs.CL2021

Parallel Composition of Weighted Finite-State Transducers

Shubho Sengupta, Vineel Pratap, Awni Hannun

Finite-state transducers (FSTs) are frequently used in speech recognition. Transducer composition is an essential operation for combining different sources of information at differ…

cs.SD2021

Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training

Wei-Ning Hsu, Anuroop Sriram, Alexei Baevski +8

Self-supervised learning of speech representations has been a very active research area but most work is focused on a single domain such as read audio books for which there exist l…

eess.AS2020354 cited

MLS: A Large-Scale Multilingual Dataset for Speech Research

Vineel Pratap, Qiantong Xu, Anuroop Sriram +2

This paper introduces Multilingual LibriSpeech (MLS) dataset, a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox an…

cs.LG202010 cited

Differentiable Weighted Finite-State Transducers

Awni Hannun, Vineel Pratap, Jacob Kahn +1

We introduce a framework for automatic differentiation with weighted finite-state transducers (WFSTs) allowing them to be used dynamically at training time. Through the separation…