README.md

metadata

language:
  - bn
pretty_name: Scraped Bengali TTS Speech Chunks
tags:
  - bengali
  - bangla
  - tts
  - text-to-speech
  - speech
  - audio
  - youtube
dataset_info:
  config_name: bengali
  features:
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: language
      dtype: string
    - name: seconds
      dtype: float64
    - name: emotion
      dtype: string
  splits:
    - name: train
      num_bytes: 52622250
      num_examples: 302
  download_size: 52506028
  dataset_size: 52622250
configs:
  - config_name: bengali
    data_files:
      - split: train
        path: bengali/train-*

Scraped Bengali TTS Speech Chunks

Single-speaker Bengali (bn) speech chunks extracted from YouTube videos, cleaned and segmented for TTS (text-to-speech) training data.

Pipeline

Each chunk was produced by:

1. Downloading source audio via yt-dlp
2. Trimming the first/last 2 minutes of each source video
3. Removing background music/noise via Demucs vocal separation
4. Splitting stereo channels into independent left/right tracks when present
5. Voice Activity Detection (Silero VAD) to find speech regions per track
6. Speaker diarization (pyannote.audio), run once on the full track; only speaker turns with ZERO overlap against any other speaker are kept, then intersected with the VAD speech regions -- chunk boundaries come from these clean single-speaker windows, not from raw VAD segments, so overlapping/crosstalk audio is excluded rather than merely down-weighted
7. Emotion tagging (Hatman/audio-emotion-detection) on each accepted chunk -- metadata only, nothing is filtered by emotion

Columns

• audio: the speech chunk, mono, 16kHz WAV
• language: ISO 639-1 language code (bn = Bengali)
• seconds: duration of the chunk in seconds
• emotion: predicted emotion label (Angry, Disgusted, Fearful, Happy, Neutral, Sad, Suprised) from Hatman/audio-emotion-detection

Config

• bengali: all Bengali-language chunks collected so far