activity
20212023
most citedGigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

216 citations · 221 across the 7 of their papers we have counts for

collaborators

7 papers

cs.MM2023

AV-SepFormer: Cross-Attention SepFormer for Audio-Visual Target Speaker Extraction

Jiuxin Lin, Xinyu Cai, Heinrich Dinkel +7

Visual information can serve as an effective cue for target speaker extraction (TSE) and is vital to improving extraction performance. In this paper, we propose AV-SepFormer, a Sep…

cs.SD2023★ 1 cited

Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Information

Jiuxin Lin, Peng Wang, Heinrich Dinkel +6

Previously, Target Speaker Extraction (TSE) has yielded outstanding performance in certain application scenarios for speech enhancement and source separation. However, obtaining au…

cs.SD2022

An empirical study of weakly supervised audio tagging embeddings for general audio representations

Heinrich Dinkel, Zhiyong Yan, Yongqing Wang +2

We study the usability of pre-trained weakly supervised audio tagging (AT) models as feature extractors for general audio representations. We mainly analyze the feasibility of tran…

cs.SD2022★ 2 cited

UniKW-AT: Unified Keyword Spotting and Audio Tagging

Heinrich Dinkel, Yongqing Wang, Zhiyong Yan +2

Within the audio research community and the industry, keyword spotting (KWS) and audio tagging (AT) are seen as two distinct tasks and research fields. However, from a technical po…

cs.SD2022

Pseudo strong labels for large scale weakly supervised audio tagging

Heinrich Dinkel, Zhiyong Yan, Yongqing Wang +2

Large-scale audio tagging datasets inevitably contain imperfect labels, such as clip-wise annotated (temporally weak) tags with no exact on- and offsets, due to a high manual label…

cs.SD2021★ 216 cited

GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

Guoguo Chen, Shuzhou Chai, Guanbo Wang +18

This paper introduces GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training, and…

cs.CL2021★ 2 cited

speechocean762: An Open-Source Non-native English Speech Corpus For Pronunciation Assessment

Junbo Zhang, Zhiwen Zhang, Yongqing Wang +6

This paper introduces a new open-source speech corpus named "speechocean762" designed for pronunciation assessment use, consisting of 5000 English utterances from 250 non-native sp…