| --- |
| language: |
| - ml |
| license: cc-by-sa-4.0 |
| task_categories: |
| - automatic-speech-recognition |
| - text-to-speech |
| tags: |
| - malayalam |
| - speech |
| - audio |
| pretty_name: Malayalam Speech Dataset (VibeVoice) |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Malayalam Speech Dataset (VibeVoice) |
|
|
| This dataset contains Malayalam speech audio files and their corresponding transcriptions, prepared for fine-tuning ASR (Automatic Speech Recognition) models like VibeVoice. |
|
|
| ## Dataset Description |
|
|
| The dataset consists of approximately 4,126 Malayalam audio clips, split into training and testing sets with a 90/10 ratio, stratified by speaker gender. |
|
|
| - **Total Audio Files**: 4,126 |
| - **Train Split**: 3,712 samples |
| - **Test Split**: 414 samples |
| - **Total Duration**: ~5-6 hours (estimated) |
| - **Format**: 16kHz WAV |
| - **Annotation**: JSON segments and split-specific `metadata.jsonl` entries. |
|
|
| ## Dataset Structure |
|
|
| The dataset is organized into `train` and `test` directories: |
| 1. `train/`: Contains 3,712 audio-JSON pairs and `metadata.jsonl`. |
| 2. `test/`: Contains 414 audio-JSON pairs and `metadata.jsonl`. |
|
|
| Each split contains: |
| - `[id].wav`: The audio file. |
| - `[id].json`: Segment information and transcription. |
| - `metadata.jsonl`: Mapping of audio files to transcriptions. |
|
|
| ### VibeVoice JSON format |
| Each audio file is accompanied by a JSON file with the following structure: |
| ```json |
| { |
| "audio_duration": 2.523, |
| "audio_path": "female_mlf_01130_00015565294.wav", |
| "segments": [ |
| { |
| "start": 0.0, |
| "end": 2.523, |
| "text": "അങ്ങനെ രണ്ടാം ലോകമഹായുദ്ധം അവസാനിച്ചു", |
| "speaker": 0 |
| } |
| ] |
| } |
| ``` |
|
|
| ### metadata.jsonl format |
| ```json |
| {"file_name": "female_mlf_01130_00015565294.wav", "transcription": "അങ്ങനെ രണ്ടാം ലോകമഹായുദ്ധം അവസാനിച്ചു"} |
| ``` |
|
|
| ## How to use |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("Arjunj/malayalam_speech", split="train") |
| |
| # Access a sample |
| sample = dataset[0] |
| print(sample["audio"]) |
| print(sample["transcription"]) |
| ``` |
|
|
| ## Source |
| This dataset was processed and collected from various Malayalam TTS/ASR sources, including OpenSLR IDs 63 and 64, formatted specifically for VibeVoice fine-tuning requirements. |
|
|
| ## License |
| Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). |
|
|