ivkond/synthetic-speech-diarization-ru

synthetic-speech-diarization-ru

Synthetic speech diarization dataset in Parquet format.

Dataset Details

• —Number of tracks: 2000
• —Sampling rate: 16000 Hz
• —Audio format: Embedded in Parquet files (Audio feature compatible)
• —Storage: Parquet format for efficient loading

Dataset Structure

The dataset contains audio tracks with speaker diarization annotations, stored directly in Parquet format.

Features

• —audio: Audio waveform (Audio feature with array and sampling_rate)
• —duration: Track duration in seconds
• —num_speakers: Number of speakers in the track
• —speakers: List of speaker segments with timestamps and text
• —speaker_volumes: Speaker volume levels
• —conversation_type: Type of conversation (dialogue, monologue, etc.)
• —difficulty: Difficulty level (easy, medium, hard)
• —has_overlaps: Whether track contains overlapping speech
• —has_simultaneous: Whether track contains simultaneous speech
• —has_noise: Whether track contains background noise

Usage

from datasets import load_dataset

# Load dataset from HuggingFace Hub directly
dataset = load_dataset("ivkond/synthetic-speech-diarization-ru")

# Access a sample
sample = dataset[0]
print(f"Duration: {sample['duration']}s")
print(f"Speakers: {sample['num_speakers']}")

Notes

• —Audio data is embedded directly in Parquet files for efficient streaming
• —No custom loading script required
• —Compatible with standard Hugging Face dataset operations