Datasets:

MeghanaKap
/

scraped_datasets

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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:

Downloading source audio via yt-dlp
Trimming the first/last 2 minutes of each source video
Removing background music/noise via Demucs vocal separation
Splitting stereo channels into independent left/right tracks when present
Voice Activity Detection (Silero VAD) to find speech regions per track
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
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