| --- |
| license: cc0-1.0 |
| task_categories: |
| - text-to-speech |
| - automatic-speech-recognition |
| language: |
| - en |
| tags: |
| - australian |
| - australian-english |
| - australian-accent |
| - accent |
| - english-accent |
| - speech |
| - voice |
| - audio |
| - tts |
| - text-to-speech |
| - asr |
| - speech-recognition |
| - voice-cloning |
| - librivox |
| - audiobook |
| - public-domain |
| pretty_name: Australian English Speech (Australian accent audio dataset, LibriVox) |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # Australian English Speech |
|
|
| An **Australian accent** speech dataset: 110 hours of Australian |
| English audio with transcripts, from the Australian titles in the |
| [LibriVox](https://librivox.org) catalogue, cut into short clips for |
| **text-to-speech**, **voice cloning** and **speech recognition**. |
|
|
| Open English speech corpora are overwhelmingly American. This one is Australian, |
| public domain, and free of any redistribution or model-release restrictions. |
|
|
| LibriVox recordings are released into the **public domain**, and the books |
| themselves are public domain, so this dataset is unencumbered: train on it, |
| redistribute it, ship models built from it. |
|
|
| ## What is in it |
|
|
| | | | |
| |---|---| |
| | clips | 61,662 | |
| | audio | 110.2 hours | |
| | readers | 214 | |
| | books | 37 | |
| | format | mono FLAC, 24 kHz | |
| | clip length | 3-15 s | |
|
|
| Each row: |
|
|
| | field | meaning | |
| |---|---| |
| | `audio` | the clip, 24 kHz mono | |
| | `text` | transcript | |
| | `reader` | LibriVox narrator's display name | |
| | `reader_id` | LibriVox reader id | |
| | `book` | book title | |
| | `author` | author(s) | |
| | `book_id` | LibriVox book id | |
| | `section` | section number within the book | |
| | `duration` | clip length in seconds | |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("ablmontazer/australian-english-speech", split="train") |
| print(ds[0]["text"], ds[0]["audio"]["sampling_rate"]) |
| ``` |
|
|
| `reader` is a stable speaker label: filter on it to get single-speaker data. |
|
|
| ## How it was built |
|
|
| 1. Australian titles taken from LibriVox's own catalogue search. |
| 2. Each section downloaded from archive.org. |
| 3. Gentle denoising with **DeepFilterNet 3** (`atten_lim_db=6`). LibriVox audio |
| is already clean, so this only shaves the hiss rather than reshaping the |
| voice. |
| 4. **Silero VAD** segmentation into 3-15 s clips that start and end on silence. |
| 5. Transcription with **faster-whisper large-v3-turbo**. |
| 6. Clips whose transcript is LibriVox boilerplate (the spoken intro and outro |
| that top and tail every section) are dropped. |
|
|
| ## Things to know before you train on it |
|
|
| - **Transcripts are machine-generated.** Whisper is good but not perfect, and |
| punctuation and capitalisation are inconsistent between clips. For anything |
| where exact text matters, re-check against the public-domain source texts. |
| - **Accent is not verified per reader.** These are the Australian titles in the |
| catalogue; LibriVox volunteers are international, so a minority of narrators |
| reading Australian books are not themselves Australian. Filter by `reader` if |
| you need a guaranteed accent. |
| - **Per-reader volume is very uneven**, from a few minutes to over ten hours. |
| Balance or cap by reader if that matters for your training. |
| - Audio quality varies with the narrator's home recording setup, and some of |
| the older recordings are effectively band-limited. |
|
|
| ## Credits |
|
|
| Every recording here was made by a LibriVox volunteer who donated it to the |
| public domain. The narrators, and the books they read, are listed in |
| `CREDITS.md`. |
|
|
