Internet Archive Scholar
Filters
























4 Hits in 2.6 sec

WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition [article]

Binbin Zhang, Hang Lv, Pengcheng Guo, Qijie Shao, Chao Yang, Lei Xie, Xin Xu, Hui Bu, Xiaoyu Chen, Chenchen Zeng, Di Wu, Zhendong Peng
2022 arXiv   pre-print

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (1.4 MB)
https://web.archive.org/web/20211021132723/https://arxiv.org/pdf/2110.03370v3.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL. The file type is application/pdf.

Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:

2021 pre-print arXiv:2110.03370v3 fatcat:lyeewdg3ffdt7oibjrbhly27ku

Other Versions

2021 pre-print
arXiv:2110.03370v1 fatcat:ghqjsq3zijekxejcv5246ia6aa
2021 pre-print
arXiv:2110.03370v2 fatcat:yo2ap2wgyna3tfqjcvc5zmekfe
2021 pre-print
arXiv:2110.03370v4 fatcat:xk7nmebz3fhnblexb5bormsmly
In this paper, we present WenetSpeech, a multi-domain Mandarin corpus consisting of 10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about 10000 hours unlabeled speech,  ...  To the best of our knowledge, WenetSpeech is the current largest open-sourced Mandarin speech corpus with transcriptions, which benefits research on production-level speech recognition.  ...  We thank Tencent Ethereal Audio Lab and Xi'an Future AI Innovation Center for providing hosting service for WenetSpeech.  ... 
arXiv:2110.03370v5 fatcat:wipuf337nbg4hjwrur4njwiw34
Open Access Multiple Versions
Citation

Binbin Zhang, Hang Lv, Pengcheng Guo, Qijie Shao, Chao Yang, Lei Xie, Xin Xu, Hui Bu, Xiaoyu Chen, Chenchen Zeng, Di Wu, Zhendong Peng. "WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition." arXiv (2022)

TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline [article]

Chengfei Li, Shuhao Deng, Yaoping Wang, Guangjing Wang, Yaguang Gong, Changbin Chen, Jinfeng Bai
2022 arXiv   pre-print

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (717.1 kB)
https://web.archive.org/web/20220628043444/https://arxiv.org/ftp/arxiv/papers/2206/2206.13135.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL. The file type is application/pdf.

This paper introduces a new corpus of Mandarin-English code-switching speech recognition--TALCS corpus, suitable for training and evaluating code-switching speech recognition systems.  ...  Using TALCS corpus, we conduct ASR experiments in two popular speech recognition toolkits to make a baseline system, including ESPnet and Wenet.  ...  WENETSPEECH [3] also provides a multidomain mandarin corpus for speech recognition, which consists of 10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about 10000 hours  ... 
arXiv:2206.13135v1 fatcat:rhldqph355a5bagwtfe55bzqw4
Citation

Chengfei Li, Shuhao Deng, Yaoping Wang, Guangjing Wang, Yaguang Gong, Changbin Chen, Jinfeng Bai. "TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline." arXiv (2022)

Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Dataset [article]

Zehui Yang, Yifan Chen, Lei Luo, Runyan Yang, Lingxuan Ye, Gaofeng Cheng, Ji Xu, Yaohui Jin, Qingqing Zhang, Pengyuan Zhang, Lei Xie, Yonghong Yan
2022 arXiv   pre-print

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (126.4 kB)
https://web.archive.org/web/20220518024323/https://arxiv.org/pdf/2203.16844v1.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL. The file type is application/pdf.

The MagicData-RAMC corpus contains 180 hours of conversational speech data recorded from native speakers of Mandarin Chinese over mobile phones with a sampling rate of 16 kHz.  ...  As a Mandarin speech dataset designed for dialog scenarios with high quality and rich annotations, MagicData-RAMC enriches the data diversity in the Mandarin speech community and allows extensive research  ...  WenetSpeech [12] is a recently released Mandarin corpus containing more than 10000 hours of speech collected from YouTube and podcasts, adopted with optical character recognition (OCR) and automatic  ... 
arXiv:2203.16844v1 fatcat:dnj2fsqxn5dj7brc5ephzktkty
Citation

Zehui Yang, Yifan Chen, Lei Luo, Runyan Yang, Lingxuan Ye, Gaofeng Cheng, Ji Xu, Yaohui Jin, Qingqing Zhang, Pengyuan Zhang, Lei Xie, Yonghong Yan. "Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Dataset." arXiv (2022)

The MSXF TTS System for ICASSP 2022 ADD Challenge [article]

Chunyong Yang, Pengfei Liu, Yanli Chen, Hongbin Wang, Min Liu
2022 arXiv   pre-print

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (100.3 kB)
https://web.archive.org/web/20220129233623/https://arxiv.org/pdf/2201.11400v1.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL. The file type is application/pdf.

We use an end to end text to speech system, and add a constraint loss to the system when training stage. The end to end TTS system is VITS, and the pre-training self-supervised model is wav2vec 2.0.  ...  This paper presents our MSXF TTS system for Task 3.1 of the Audio Deep Synthesis Detection (ADD) Challenge 2022.  ...  The wav2vec 2.0 are trained using the open source data WenetSpeech [14] , a 10000+ hours multi-domain mandarin corpus.  ... 
arXiv:2201.11400v1 fatcat:luagwlz4fretfg6dfngmfx3ree
Open Access
Citation

Chunyong Yang, Pengfei Liu, Yanli Chen, Hongbin Wang, Min Liu. "The MSXF TTS System for ICASSP 2022 ADD Challenge." arXiv (2022)