5.2k citations · 5.6k across the 17 of their papers we have counts for
5 papers · 1 filter
Unsupervised ASR via Cross-Lingual Pseudo-Labeling
Tatiana Likhomanenko, Loren Lugosch, Ronan Collobert
Recent work has shown that it is possible to train an automatic speech recognition (ASR) system using only unpaired audio and text. Existing unsupervised AS…
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…
Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition
Vimal Manohar, Tatiana Likhomanenko, Qiantong Xu +5
In this paper, we introduce the Kaizen framework that uses a continuously improving teacher to generate pseudo-labels for semi-supervised speech recognition (ASR). The proposed app…
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…
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters
Vineel Pratap, Anuroop Sriram, Paden Tomasello +4
We study training a single acoustic model for multiple languages with the aim of improving automatic speech recognition (ASR) performance on low-resource languages, and over-all si…