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

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arxiv 2203.16844 v1 pith:4X56L55A submitted 2022-03-31 cs.CL eess.AS

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

Zehui Yang , Yifan Chen , Lei Luo , Runyan Yang , Lingxuan Ye , Gaofeng Cheng , Ji Xu , Yaohui Jin
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Qingqing Zhang Pengyuan Zhang Lei Xie Yonghong Yan
This is my paper
classification cs.CL eess.AS
keywords speechmagicdata-ramcmandarindatasetconversationalrichannotateddata
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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