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khursanirevo/multiturn_ks

khursanirevo/multiturn_ks Dataset Description Multiturn dialogue dataset with speaker-separated stereo audio and multi-language transcripts from 139 YouTube videos. Features Audio: Stereo audio with speaker separation (speaker 0 = left channel, speaker 1 = right channel) Segments: Speaker turn-level annotations with timestamps for English and Malay Multi-language: Transcripts in 9 languages (en, ms, zh-Hans, zh-Hant, ru, id, ar, ja, ko) Video ID:… See the full description on the dataset page: https://huggingface.co/datasets/khursanirevo/multiturn_ks.

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Dataset Card

khursanirevo/multiturn_ks

Dataset Description

Multiturn dialogue dataset with speaker-separated stereo audio and multi-language transcripts from 139 YouTube videos.

Features

  • Audio: Stereo audio with speaker separation (speaker 0 = left channel, speaker 1 = right channel)
  • Segments: Speaker turn-level annotations with timestamps for English and Malay
  • Multi-language: Transcripts in 9 languages (en, ms, zh-Hans, zh-Hant, ru, id, ar, ja, ko)
  • Video ID: YouTube video identifier for each chunk
  • Chunking: 30-second chunks with 0.5s overlap

Columns

  • audio: Playable stereo audio (24kHz)
  • video_id: YouTube video identifier
  • sentence: Full transcript for the chunk (English)
  • segments_en: JSON list of English speaker turns [{speaker, start, end, text}]
  • segments_ms: JSON list of Malay speaker turns [{speaker, start, end, text}]
  • total_speakers: Number of speakers in chunk (typically 2)
  • sentence_ms, sentence_en, etc.: Transcripts in each language

Usage

python
from datasets import load_dataset
import json

dataset = load_dataset("khursanirevo/multiturn_ks")

# Access audio and segments
chunk = dataset[0]
audio = chunk["audio"]  # Stereo audio array
video_id = chunk["video_id"]  # YouTube video ID
segments_en = json.loads(chunk["segments_en"])  # English speaker turns
segments_ms = json.loads(chunk["segments_ms"])  # Malay speaker turns

print(f"From video: {video_id}")
for seg in segments_en:
    speaker = seg['speaker']
    text = seg['text']
    print(f"Speaker {speaker} (EN): {text}")

for seg in segments_ms:
    speaker = seg['speaker']
    text = seg['text']
    print(f"Speaker {speaker} (MS): {text}")

Audio Format

  • Format: WAV (PCM)
  • Sample rate: 24kHz
  • Channels: 2 (stereo, speaker separation)
  • Bit depth: 32-bit float

Speaker Detection

Speakers are detected using RMS energy analysis:

  • Channel 0 (left): Speaker 0
  • Channel 1 (right): Speaker 1

Languages

Supported languages:

  • English (en)
  • Malay (ms)
  • Chinese Simplified (zh-Hans)
  • Chinese Traditional (zh-Hant)
  • Russian (ru)
  • Indonesian (id)
  • Arabic (ar)
  • Japanese (ja)
  • Korean (ko)

Dataset Statistics

  • Total videos: 139
  • Total chunks: 26383
  • Max chunk duration: 30s
  • Overlap: 0.5s

Source

Created from YouTube videos with dialogue separation using DialogueSidon model.

License

CC-BY-4.0