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20202025
most citedStreaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition

13 citations · 16 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.SD2023

Accurate and Reliable Confidence Estimation Based on Non-Autoregressive End-to-End Speech Recognition System

Xian Shi, Haoneng Luo, Zhifu Gao +2

Estimating confidence scores for recognition results is a classic task in ASR field and of vital importance for kinds of downstream tasks and training strategies. Previous end-to-e…

cs.SD20234 cited

FunASR: A Fundamental End-to-End Speech Recognition Toolkit

Zhifu Gao, Zerui Li, Jiaming Wang +8

This paper introduces FunASR, an open-source speech recognition toolkit designed to bridge the gap between academic research and industrial applications. FunASR offers models train…

cs.SD2021

Boundary and Context Aware Training for CIF-based Non-Autoregressive End-to-end ASR

Fan Yu, Haoneng Luo, Pengcheng Guo +6

Continuous integrate-and-fire (CIF) based models, which use a soft and monotonic alignment mechanism, have been well applied in non-autoregressive (NAR) speech recognition with com…

cs.SD202013 cited

Streaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition

Shiliang Zhang, Zhifu Gao, Haoneng Luo +4

Recently, streaming end-to-end automatic speech recognition (E2E-ASR) has gained more and more attention. Many efforts have been paid to turn the non-streaming attention-based E2E-…

cs.SD2020

Simplified Self-Attention for Transformer-based End-to-End Speech Recognition

Haoneng Luo, Shiliang Zhang, Ming Lei +1

Transformer models have been introduced into end-to-end speech recognition with state-of-the-art performance on various tasks owing to their superiority in modeling long-term depen…