README.md

metadata

dataset_info:
  features:
    - name: source
      dtype: string
    - name: filename
      dtype: string
    - name: order_index
      dtype: string
    - name: link
      dtype: string
    - name: transcript_whisper
      dtype: string
    - name: audio
      dtype: audio
    - name: c50
      dtype: float32
    - name: snr
      dtype: float32
    - name: speech_duration
      dtype: float32
    - name: emotion_emotion2vec
      dtype: string
    - name: transcript_sensevoice
      dtype: string
    - name: emotion_sensevoice
      sequence: string
    - name: event_sensevoice
      sequence: string
  splits:
    - name: train
      num_bytes: 507480914420.836
      num_examples: 2229346
  download_size: 589102038968
  dataset_size: 507480914420.836
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
task_categories:
  - automatic-speech-recognition
  - audio-classification
language:
  - zh
  - yue

Cantonese Radio Pseudo-Transcription Dataset

• Contains 14k hours of audio sourced from Archive.org
• Columns
  • order_index: Represents the order of the audio compared to those from the same filename
  • link: Link of the original full audio
  • transcript_whisper: Transcribed using Scrya/whisper-large-v2-cantonese with alvanlii/whisper-small-cantonese for speculative decoding
  • transcript_sensevoice: Transcribed using FunAudioLLM/SenseVoiceSmall
    • used OpenCC to convert to traditional chinese
    • isolated event tags to event_sensevoice
    • isolated emotion tags to emotion_sensevoice
  • snr: Signal-to-noise ratio, extracted from ylacombe/brouhaha-best
  • c50: Speech clarity, extracted from ylacombe/brouhaha-best
  • emotion: Emotion, extracted from emotion2vec/emotion2vec_plus_large
  • Note that id does not reflect the ordering of the audio within the same video
• Processing
  • The full audio is split using WhisperX, using Scrya/whisper-large-v2-cantonese
    • it is split in <30s chunks and according to speakers
  • No filtering or additional audio processing was done for this dataset
    • Filtering is recommended for your own use