| --- |
| language: |
| - en |
| task_categories: |
| - text-to-speech |
| tags: |
| - synthetic |
| - tts |
| - expressive-speech |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata.jsonl |
| --- |
| |
| # Maya1 expressive English TTS dataset (synthetic) |
|
|
| **Samples:** 37 | **Total audio:** 0.062 hours | **Mean duration:** 6.04 s | **Format:** 24000 Hz WAV |
|
|
| ## Purpose and generation method |
| Synthetic speech for TTS research. Each record was produced in two stages: a small instruction model |
| (`Qwen/Qwen3-0.6B`) wrote an English utterance and inline-tag placement; the pipeline assigned controlled voice attributes |
| and rendered them as a voice description. Maya1 (Q8_0 GGUF, `audio-cpp/audio.cpp-gguf/Maya1-GGUF/maya1-q8_0.gguf`) then ran through the audio.cpp runtime |
| (v0.9.0, CUDA) to render the audio. |
| Voice design uses a controlled attribute vocabulary (realistic: age, gender, accent, pitch, timbre, pacing, emotion and intensity, domain, role, register; creative: character plus the same base attributes) rendered into a fixed descriptive string passed via `instruct=`. The sampled attributes are stored in `voice_attributes`. |
|
|
| ## Scope |
| English only (default). 24 kHz WAV, sample rate and duration validated per file after generation. |
|
|
| ## Inline tag convention |
| Tags are angle-bracket tokens placed inline in `text` at the point they should affect delivery. |
| Allowlist (20): <angry>, <appalled>, <chuckle>, <cry>, <curious>, <disappointed>, <excited>, <exhale>, <gasp>, <giggle>, <gulp>, <laugh>, <laugh_harder>, <mischievous>, <sarcastic>, <scream>, <sigh>, <sing>, <snort>, <whisper>. Many records contain no tag. `inline_tags` lists the tags actually found in `text`. |
|
|
| ## Schema (`metadata.jsonl`) |
| `id`, `text`, `audio` (relative path), `duration_seconds`, `sample_rate`, `channels`, `language`, `voice_description`, |
| `voice_design_id`, `voice_attributes`, `topic`, `style`, `inline_tags`, `model_name`, `quantization`, `model_filename`, `runtime_version`, |
| `qwen_model`, `voice_description_source`, `generation_settings`, `seed`, `generation_wall_seconds`, `generation_status`, `created_at`. |
| `texts.jsonl` holds all accepted text records (some may have no audio yet); `generation_errors.jsonl` logs failed attempts. |
|
|
| ## Loading |
| ```python |
| from huggingface_hub import snapshot_download |
| from datasets import load_dataset, Audio |
| root = snapshot_download("Shadow0482/test-v1", repo_type="dataset") |
| ds = load_dataset("json", data_files=root + "/metadata.jsonl", split="train") |
| ds = ds.map(lambda r: {"audio": root + "/" + r["audio"]}).cast_column("audio", Audio(sampling_rate=24000)) |
| print(ds[0]["text"], ds[0]["voice_description"]) |
| ``` |
|
|
| ## Known limitations |
| All text and audio are model-generated: pronunciation, prosody, accent and tag realisation can deviate from the written |
| description; invented content is not factual. Automatic validation is heuristic (duration, silence, format), not human review. |
| Near-duplicate filtering is lexical. Quality of a 0.6B-parameter text generator is limited. |
|
|
| ## Licenses and notices |
| Maya1 is Apache-2.0 and its bundled SNAC decoder is MIT (as stated in the task brief; confirm on the upstream model cards). |
| See the model cards of `Qwen/Qwen3-0.6B` and the audio.cpp repository for their terms. **No license has been declared for this |
| dataset**; review upstream model/output terms before choosing one. |
|
|
| ## Synthetic-data disclosure |
| This dataset consists entirely of synthetic speech and synthetic text. It does not contain recordings of real people. |
|
|
