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20132023
most citedWavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

1.9k citations · 3.5k across the 108 of their papers we have counts for

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Showing 2020Show all

23 papers · 1 filter

eess.AS2020★ 2 cited

Listen, Look and Deliberate: Visual context-aware speech recognition using pre-trained text-video representations

Shahram Ghorbani, Yashesh Gaur, Yu Shi +1

In this study, we try to address the problem of leveraging visual signals to improve Automatic Speech Recognition (ASR), also known as visual context-aware ASR (VC-ASR). We explore…

eess.AS2020

Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis

Desh Raj, Pavel Denisov, Zhuo Chen +11

Multi-speaker speech recognition of unsegmented recordings has diverse applications such as meeting transcription and automatic subtitle generation. With technical advances in syst…

eess.AS2020

Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition

Zhong Meng, Sarangarajan Parthasarathy, Eric Sun +7

The external language models (LM) integration remains a challenging task for end-to-end (E2E) automatic speech recognition (ASR) which has no clear division between acoustic and la…

cs.SD2020★ 42 cited

Streaming end-to-end multi-talker speech recognition

Liang Lu, Naoyuki Kanda, Jinyu Li +1

End-to-end multi-talker speech recognition is an emerging research trend in the speech community due to its vast potential in applications such as conversation and meeting transcri…

cs.SD2020★ 3 cited

Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer

Sanyuan Chen, Yu Wu, Zhuo Chen +3

With its strong modeling capacity that comes from a multi-head and multi-layer structure, Transformer is a very powerful model for learning a sequential representation and has been…

eess.AS2020★ 6 cited

Microsoft Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2020

Xiong Xiao, Naoyuki Kanda, Zhuo Chen +10

This paper describes the Microsoft speaker diarization system for monaural multi-talker recordings in the wild, evaluated at the diarization track of the VoxCeleb Speaker Recogniti…