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20192021
most citedAccent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings

11 citations · 28 across the 10 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL20212 cited

Improved Language Identification Through Cross-Lingual Self-Supervised Learning

Andros Tjandra, Diptanu Gon Choudhury, Frank Zhang +6

Language identification greatly impacts the success of downstream tasks such as automatic speech recognition. Recently, self-supervised speech representations learned by wav2vec 2.…

cs.CL2021

Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion

Duc Le, Mahaveer Jain, Gil Keren +9

How to leverage dynamic contextual information in end-to-end speech recognition has remained an active research area. Previous solutions to this problem were either designed for sp…

cs.CL20201 cited

Improving RNN Transducer Based ASR with Auxiliary Tasks

Chunxi Liu, Frank Zhang, Duc Le +3

End-to-end automatic speech recognition (ASR) models with a single neural network have recently demonstrated state-of-the-art results compared to conventional hybrid speech recogni…

cs.CL20205 cited

Contextualizing ASR Lattice Rescoring with Hybrid Pointer Network Language Model

Da-Rong Liu, Chunxi Liu, Frank Zhang +3

Videos uploaded on social media are often accompanied with textual descriptions. In building automatic speech recognition (ASR) systems for videos, we can exploit the contextual in…

cs.CL2019

Training ASR models by Generation of Contextual Information

Kritika Singh, Dmytro Okhonko, Jun Liu +8

Supervised ASR models have reached unprecedented levels of accuracy, thanks in part to ever-increasing amounts of labelled training data. However, in many applications and locales,…