TY - JOUR
T1 - Open Source MagicData-RAMC
T2 - 23rd Annual Conference of the International Speech Communication Association, INTERSPEECH 2022
AU - Yang, Zehui
AU - Chen, Yifan
AU - Luo, Lei
AU - Yang, Runyan
AU - Ye, Lingxuan
AU - Cheng, Gaofeng
AU - Xu, Ji
AU - Jin, Yaohui
AU - Zhang, Qingqing
AU - Zhang, Pengyuan
AU - Xie, Lei
AU - Yan, Yonghong
N1 - Publisher Copyright:
Copyright © 2022 ISCA.
PY - 2022
Y1 - 2022
N2 - This paper introduces a high-quality rich annotated Mandarin conversational (RAMC) speech dataset called MagicData-RAMC. 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. The dialogs in MagicData-RAMC are classified into 15 diversified domains and tagged with topic labels, ranging from science and technology to ordinary life. Accurate transcription and precise speaker voice activity timestamps are manually labeled for each sample. Speakers' detailed information is also provided. 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 on a series of speech-related tasks, including automatic speech recognition, speaker diarization, topic detection, keyword search, text-to-speech, etc. We also conduct several relevant tasks and provide experimental results to help evaluate the dataset.
AB - This paper introduces a high-quality rich annotated Mandarin conversational (RAMC) speech dataset called MagicData-RAMC. 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. The dialogs in MagicData-RAMC are classified into 15 diversified domains and tagged with topic labels, ranging from science and technology to ordinary life. Accurate transcription and precise speaker voice activity timestamps are manually labeled for each sample. Speakers' detailed information is also provided. 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 on a series of speech-related tasks, including automatic speech recognition, speaker diarization, topic detection, keyword search, text-to-speech, etc. We also conduct several relevant tasks and provide experimental results to help evaluate the dataset.
KW - Mandarin corpus
KW - dialog scenario
KW - keyword search
KW - speaker diarization
KW - speech recognition
UR - http://www.scopus.com/inward/record.url?scp=85140096266&partnerID=8YFLogxK
U2 - 10.21437/Interspeech.2022-729
DO - 10.21437/Interspeech.2022-729
M3 - 会议文章
AN - SCOPUS:85140096266
SN - 2308-457X
VL - 2022-September
SP - 1736
EP - 1740
JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Y2 - 18 September 2022 through 22 September 2022
ER -