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--- |
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task_categories: |
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- automatic-speech-recognition |
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language: |
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- en |
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- zh |
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tags: |
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- speaker-diarization |
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- meeting-transcription |
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- bilingual |
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license: apache-2.0 |
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--- |
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# Dataset Card for Multi-Talker-SD |
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### Dataset Description |
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**Multi-Talker-SD** is a large-scale bilingual (English–Mandarin) multi-speaker meeting dataset designed to support research on **speaker diarization** and **meeting transcription**. |
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- **Size:** 1,000 simulated meetings |
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- **Participants per meeting:** 10–30 speakers |
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- **Average duration:** ~20 minutes per meeting, up to one hour |
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- **Languages:** English, Mandarin (code-switching possible) |
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- **Audio characteristics:** realistic speaker overlap, turn-taking patterns, reverberation, and noise injection |
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- **Metadata:** speaker gender, language, session type, utterance timing |
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The audio is synthesized using utterances from **AIShell-1** (Mandarin) and **LibriSpeech** (English), with added noise and reverberation to approximate real meeting conditions. |
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- **Curated by:** AISG Speech Lab |
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- **License:** Apache-2.0 |
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### Dataset Sources |
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- **Repository:** [GitHub - Multi-Talker-SD](https://github.com/wyhzhen6/MULTI-TALKER-SD) |
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- **Dataset on HF Hub:** [Multi-Talker-SD](https://huggingface.co/datasets/yihao005/Multi-Talker-SD) |
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### Direct Use |
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- Research on **speaker diarization** under multilingual and overlapped speech conditions |
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- **Meeting transcription** in bilingual settings |
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- Controlled experiments on the effects of speaker metadata (gender, language, etc.) |
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- Training and evaluation of **overlap-aware diarization models** |
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## Dataset Structure |
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- **Audio files (.wav):** multi-speaker simulated meetings |
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- **RTTM files:** diarization annotations with speaker labels and timestamps |
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- **Metadata files:** speaker profiles including gender, language, and session type |
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Each example contains: |
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- Meeting ID |
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- List of speakers (with attributes) |
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- Audio waveform |
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- RTTM segmentation |
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## Dataset Creation |
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### Source Data |
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- **English speech:** LibriSpeech |
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- **Mandarin speech:** AIShell-1 |
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- **Noise sources:** point-source and diffuse-field noise corpora |
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- **Processing:** audio mixing, reverberation simulation, overlap control |
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### Personal and Sensitive Information |
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No personally identifiable or sensitive data is included. All speech is sourced from **public corpora**. |
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