activity
20182022
most citedRecent Developments on ESPnet Toolkit Boosted by Conformer

40 citations · 88 across the 20 of their papers we have counts for

collaborators

22 papers

cs.CL2022

A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding

Yifan Peng, Siddhant Arora, Yosuke Higuchi +6

Collecting sufficient labeled data for spoken language understanding (SLU) is expensive and time-consuming. Recent studies achieved promising results by using pre-trained models in…

cs.CL2022

SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning

Tzu-hsun Feng, Annie Dong, Ching-Feng Yeh +11

We present the SUPERB challenge at SLT 2022, which aims at learning self-supervised speech representation for better performance, generalization, and efficiency. The challenge buil…

cs.SD2022

End-to-End Integration of Speech Recognition, Dereverberation, Beamforming, and Self-Supervised Learning Representation

Yoshiki Masuyama, Xuankai Chang, Samuele Cornell +2

Self-supervised learning representation (SSLR) has demonstrated its significant effectiveness in automatic speech recognition (ASR), mainly with clean speech. Recent work pointed o…

cs.SD20221 cited

End-to-End Integration of Speech Recognition, Speech Enhancement, and Self-Supervised Learning Representation

Xuankai Chang, Takashi Maekaku, Yuya Fujita +1

This work presents our end-to-end (E2E) automatic speech recognition (ASR) model targetting at robust speech recognition, called Integraded speech Recognition with enhanced speech…

eess.AS2022

End-to-End Multi-speaker ASR with Independent Vector Analysis

Robin Scheibler, Wangyou Zhang, Xuankai Chang +2

We develop an end-to-end system for multi-channel, multi-speaker automatic speech recognition. We propose a frontend for joint source separation and dereverberation based on the in…

cs.CL20223 cited

SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities

Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang +14

Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervi…