Create README.md

README.md

@@ -0,0 +1,88 @@
+---
+license: apache-2.0
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+language:
+- ru
+size_categories:
+- 100K<n<1M
+pretty_name: IGM YouTube Dataset
+tags:
+- audio
+- text
+---
+
+# IGM YouTube Audio Dataset
+
+## Dataset Description
+
+This dataset contains 220 hours of processed audio segments extracted from the IGM YouTube channel with corresponding metadata. Each audio file represents a segment from IGM's educational videos and lectures, processed at 44.1kHz sample rate.
+
+### Dataset Summary
+
+- **Language**: Russian
+- **Task**: TTS, ASR, Quality Assessment
+- **Audio format**: MP3, 44.1kHz sample rate
+- **Structure**: Segmented audio files with JSON metadata
+- **Source**: IGM YouTube channel content
+
+## Dataset Structure
+
+### Data Fields
+
+#### Basic Information
+- `audio`: Audio data (44.1kHz sample rate, MP3 format)
+- `file_name`: Name of the audio segment file (format: `<original_name>_<idx>.mp3`)
+- `segment_index`: Index of the audio segment within the original video
+- `original_name`: Original name of the YouTube video recording
+
+#### Transcription and Timing
+- `text`: Transcribed text of the audio segment
+- `start`: Start time of the segment in seconds
+- `end`: End time of the segment in seconds
+- `words`: Word-level timestamps and confidence scores
+
+#### Speaker Information
+- `speaker`: Speaker identifier (e.g., "SPEAKER_00")
+
+#### Quality Metrics
+- `emos_overall`: EMOS overall quality score
+- `noise_confidence`: Noise detection confidence
+
+![design](https://huggingface.co/datasets/ESpeech/ESpeech-igm/resolve/main/mos.png)
+
+#### Segment Structure
+- `num_sentences`: Number of sentences (for merged segments)
+- `original_segments`: Original subsegments data (for merged segments)
+
+#### VAD (Voice Activity Detection)
+- `vad_trimmed`: Whether VAD trimming was applied
+- `vad_start`: VAD start time
+- `trim_ratio`: Ratio of trimmed audio
+
+### Data Splits
+- **Train**: All available YouTube video segments
+
+## Dataset Creation
+
+### Source Data
+The dataset consists of audio content extracted from the IGM YouTube channel. IGM produces educational content, lectures, and discussions primarily in Russian. Each YouTube video has been processed and segmented into multiple audio clips, with each segment saved as a separate MP3 file along with its transcription and metadata.
+
+## Usage
+
+### Loading the Dataset
+Load and extract the tar.aa and tar.ab archive files using:
+```bash
+cat igm_archive.tar.aa igm_archive.tar.ab > igm_archive.tar && tar -xf igm_archive.tar
+```
+
+### Citation Information
+```bibtex
+@dataset{igm_youtube_audio_dataset,
+  title={IGM YouTube Audio Dataset},
+  author={Denis Petrov},
+  year={2025},
+  url={https://huggingface.co/datasets/ESpeech/ESpeech-igm/}
+}
+```