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README.md

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+---
+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 in `.wav` format, each accompanied by a `.json` file containing the transcription and segment information.
+
+- **Total Audio Files**: 4,126
+- **Total Duration**: ~5-6 hours (estimated)
+- **Format**: 16kHz WAV
+- **Annotation**: JSON segments and `metadata.jsonl` entry for Hugging Face `datasets` library compatibility.
+
+## Dataset Structure
+
+Each sample in the dataset is named with a consistent pattern (e.g., `female_mlf_01130_00015565294`) and has two associated files:
+1. `[id].wav`: The audio file.
+2. `[id].json`: Segment information and transcription.
+
+Additionally, a `metadata.jsonl` file is provided at the root for easy loading via the `datasets` library.
+
+### 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).