| # VOA PT-BR Raw Audio Dataset | |
| ## Dataset Description | |
| This dataset contains raw audio chunks processed directly with Whisper (without VAD preprocessing). | |
| Each chunk has an audio file (.wav) and associated metadata including: | |
| - Raw transcription (automated using Whisper) | |
| - Duration | |
| - Start and end times | |
| - Language (pt-br) | |
| ## Usage | |
| This dataset is intended for: | |
| 1. Manual review and correction of transcriptions | |
| 2. Evaluation of direct transcription quality | |
| 3. Fine-tuning of ASR models for Portuguese | |
| 4. Future comparison with VAD preprocessed audio | |
| ## Dataset Structure | |
| - `audio/`: Contains WAV files of audio chunks | |
| - `metadata.json`: Contains complete metadata for all chunks | |
| - `metadata.csv`: CSV version of the complete metadata | |
| - `simple_dataset.csv`: Simplified version with just audio and transcription columns | |
| - `dataset_dict.json`: Dataset in HuggingFace compatible format | |
| ## Loading the Dataset | |
| You can load this dataset using the HuggingFace Datasets library: | |
| ```python | |
| from datasets import load_dataset | |
| # Load from the Hub | |
| dataset = load_dataset("voa-engines/audio-review-raw") | |
| # Access the first example | |
| example = dataset["train"][0] | |
| print(f"Audio file: {example['audio']}") | |
| print(f"Transcription: {example['transcription']}") | |
| ``` | |
| ## Processing Information | |
| The audio files were processed using the following approach: | |
| - Direct Whisper transcription without VAD preprocessing | |
| - Long audio files (>30s) were chunked into 30-second segments | |
| - Original audio file structure maintained | |
| Created on: 2025-04-04 | |