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.
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 identifiersentence: 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
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
