| --- |
| license: apache-2.0 |
| language: |
| - en |
| task_categories: |
| - text-to-speech |
| tags: |
| - synthetic |
| - tts |
| - voice-cloning |
| - omnivoice |
| pretty_name: ic-tts |
| --- |
| |
| # ic-tts |
|
|
| Synthetic speech dataset: LLM-written text, spoken by **OmniVoice** (voice cloning from reference audio). |
|
|
| | | | |
| |---|---| |
| | Utterances | 395 | |
| | Total duration | 1.00 h | |
| | Mean / min / max length | 9.1s / 3.5s / 15.2s | |
| | Sample rate | 24000 Hz mono, FLAC | |
| | Language | English | |
| | Reference voices | 1 | |
|
|
| ## Pipeline |
| 1. Text: `Qwen/Qwen2.5-0.5B-Instruct` prompted with random topic/style/length combos, cleaned and de-duplicated -> `texts.json`. |
| 2. Audio: OmniVoice (0.6B, GGUF f16) through [audio.cpp](https://github.com/0xShug0/audio.cpp) v0.9.1, zero-shot voice clone, 2x T4 in parallel. |
| 3. Basic filtering: clips that are too short or whose duration is implausible for the text length are dropped. |
|
|
| ## Files |
| - `audio/` - audio clips |
| - `metadata.jsonl` - one row per clip: `id`, `text`, `path`, `duration` (seconds), `sample_rate`, `ref_voice` (`file_name` duplicates `path` for the HF audio viewer) |
| - `texts.json` - all generated texts (including any not synthesized) |
|
|
| ## Usage |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Shadow0482/ic-tts", split="train") |
| print(ds[0]["text"], ds[0]["duration"]) |
| ``` |
|
|
| ## Notes and limitations |
| - Fully synthetic. Text can contain LLM errors or odd phrasing; speech can contain TTS artifacts. No manual verification was done. |
| - The cloned voice(s) come from reference recordings. Only use voices you have the right/consent to clone, and check the licenses of the models used (Qwen, OmniVoice) before commercial use. |
|
|
