activity
20182026
most citedA CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition

32 citations · 102 across the 19 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2026

FA-Bench: A Benchmark for Phone- and Word-Level Timestamp Accuracy in Forced Alignment and ASR on Clean and Noisy Speech

Wei Chu, Yuanzhe Dong, Ke Tan +11

Forced alignment estimates the timestamps of each word, phone or character in speech given its transcript. Published comparisons normalize transcripts, split the data and match bou…

cs.CL2025

OleSpeech-IV: A Large-Scale Multispeaker and Multilingual Conversational Speech Dataset with Diverse Topics

Wei Chu, Yuanzhe Dong, Ke Tan +7

OleSpeech-IV dataset is a large-scale multispeaker and multilingual conversational speech dataset with diverse topics. The audio content comes from publicly-available English podca…

cs.CL2023★ 32 cited

A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition

Ruchao Fan, Wei Chu, Peng Chang +1

Recently, end-to-end models have been widely used in automatic speech recognition (ASR) systems. Two of the most representative approaches are connectionist temporal classification…

cs.CL2019★ 23 cited

Improving Generalization of Transformer for Speech Recognition with Parallel Schedule Sampling and Relative Positional Embedding

Pan Zhou, Ruchao Fan, Wei Chen +1

Transformer has shown promising results in many sequence to sequence transformation tasks recently. It utilizes a number of feed-forward self-attention layers to replace the recurr…

cs.CL2018★ 6 cited

An Online Attention-based Model for Speech Recognition

Ruchao Fan, Pan Zhou, Wei Chen +2

Attention-based end-to-end models such as Listen, Attend and Spell (LAS), simplify the whole pipeline of traditional automatic speech recognition (ASR) systems and become popular i…