Final metadata, texts, config and dataset card

README.md

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+---
+language:
+- en
+task_categories:
+- text-to-speech
+tags:
+- synthetic
+- speech
+- voice-cloning
+- tts
+size_categories:
+- n<1K
+---
+
+# Synthetic single-speaker speech dataset (OmniVoice voice clone)
+
+40 utterances, 0.07 hours of audio, 24000 Hz, mono, PCM 16-bit WAV.
+
+## Voice-cloning disclosure
+All audio is **synthetic speech** generated by a text-to-speech model that clones the voice of a reference
+recording supplied by the dataset author. The speech is not a recording of a human reading these sentences.
+Only use or redistribute it if the reference speaker has consented to this use and your use complies with the
+upstream model licenses. Do not use it to impersonate people or to deceive.
+
+## How it was made
+1. **Text**: generated with `Qwen/Qwen2.5-0.5B-Instruct` (instruction prompts over varied topics, tones and forms; filtered for
+   length, digits, symbols, boilerplate, a coarse unsafe-word list and near-duplicates). The text is model-written
+   and may contain factual errors; it is intended as speech material, not as facts.
+2. **Fine-grained control markup** (added by code after the text was written, not by the LLM):
+   non-verbal tags (e.g. `[laughter]`, `[sigh]`) on about 35% of texts, balanced across tag types and
+   placed at commas or the end of the sentence; pronunciation overrides on about 25% of texts
+   (English: CMU phonemes for words with a single dictionary pronunciation; Chinese: pinyin with tone number).
+   Observed in this dataset: 14 clips with a non-verbal tag ({'[confirmation-en]': 3, '[dissatisfaction-hnn]': 2, '[laughter]': 3, '[sigh]': 2, '[surprise-yo]': 1, '[question-en]': 1, '[question-oh]': 1, '[surprise-wa]': 1}), 10 clips with pronunciation overrides.
+   `text_plain` is the same sentence without any markup.
+3. **Speech**: OmniVoice 0.6B (`OmniVoice-0.6B (omnivoice-f16.gguf via audio.cpp v0.9.1)`) run through the audio.cpp runtime v0.9.1, cloning one reference voice
+   (steps=20, guidance=2.0, speed=1.0, per-sample seed = 1234 + sample index).
+4. **Validation**: each clip is decoded, checked for duration, silence, NaNs and a characters-per-second plausibility window,
+   and stored together with its text. Duration is measured from the saved audio, not estimated.
+   Whether the model actually honoured each tag or pronunciation override is NOT verified automatically.
+
+## Layout
+```
+audio/000001.wav, ...
+metadata.jsonl           one JSON object per clip
+texts.jsonl              all generated texts (including texts not synthesized)
+generation_errors.jsonl  failed or retried jobs
+config.json              generation configuration (no secrets)
+```
+
+## Schema (`metadata.jsonl`)
+| field | meaning |
+|---|---|
+| id | stable 6-digit sample id (matches the text id in `texts.jsonl`) |
+| file_name, audio_path | relative audio path (`file_name` is what `datasets` AudioFolder reads) |
+| text | the string that was synthesized (may contain tags / pronunciation overrides) |
+| text_plain | the same sentence with all markup removed (use for ASR-style transcripts) |
+| control_tags | non-verbal tags present in `text` |
+| pron_overrides | list of pronunciation overrides applied (word/char and phonemes/pinyin) |
+| duration_seconds, sample_rate | measured from the saved file |
+| language, speaker_id, voice_description | language code, constant speaker id, free-text voice description |
+| style, topic, form | prompt attributes used when the text was generated |
+| model_name, text_model, seed, tts_steps | generation provenance |
+| generation_status | `ok` |
+
+## Loading
+```python
+from datasets import load_dataset
+ds = load_dataset("Shadow0482/tts-v2", split="train")   # AudioFolder-style: metadata.jsonl + audio/
+print(ds[0]["text"], ds[0]["audio"]["sampling_rate"])
+```
+(The loading snippet follows the standard `datasets` AudioFolder convention; it has not been executed by the generator.)
+
+## Intended uses
+Research and prototyping for TTS / voice-cloning pipelines, controllable-TTS experiments, speaker-adaptation studies.
+
+## Limitations
+* Single synthetic voice; prosody comes from a diffusion TTS model and may contain artifacts, mispronunciations or
+  occasional truncation that automated checks cannot fully catch.
+* Tags and pronunciation overrides are requests to the TTS model; the effect strength varies and is not measured.
+* Small-LLM text: limited diversity, simple vocabulary, occasional awkward phrasing.
+* The unsafe-word filter is coarse; review before use in sensitive settings.
+
+## Licensing
+No license is declared by this card because none has been verified for the combined artifact. Upstream components:
+* OmniVoice weights via the audio.cpp GGUF package (`audio-cpp/audio.cpp-gguf`; the repo's table lists Apache-2.0 for this package) - verify before redistribution.
+* Text model `Qwen/Qwen2.5-0.5B-Instruct` (Qwen2.5 Instruct small models are published under Apache-2.0 on their model cards) - verify.
+* audio.cpp runtime: Apache-2.0.
+The reference speaker's rights are separate and are the responsibility of the dataset author.
+
+## Generation summary
+Valid audio: 0.068 h (target 0.05 h, delta +0.018 h); clips: 40; mean duration 6.123 s; this session: 0:05:28 wall time, 0.7x realtime aggregate. Failed/pruned records are in generation_errors.jsonl.

config.json

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+{
+  "TARGET_HOURS": 0.05,
+  "NUM_TTS_WORKERS": 10,
+  "TTS_BATCH_SIZE": 4,
+  "LLM_BATCH_SIZE": 32,
+  "MAX_TTS_VRAM_GB": 7,
+  "QWEN_MODEL_SIZE": "0.5B",
+  "AUDIO_FORMAT": "wav",
+  "SAMPLE_RATE": 24000,
+  "HF_DATASET_REPO": "Shadow0482/tts-v2",
+  "HF_PRIVATE": true,
+  "ENABLE_HF_UPLOAD": true,
+  "UPLOAD_EVERY_N_SAMPLES": 1500,
+  "UPLOAD_BATCH_SIZE": 500,
+  "LANGUAGE": "en",
+  "ACCENT": "",
+  "SPEAKER_ID": "speaker_0001",
+  "SPEAKER_DESCRIPTION": "",
+  "SEED": 1234,
+  "GEN_MAX_NEW_TOKENS": 384,
+  "MIN_WORDS": 5,
+  "MAX_WORDS": 38,
+  "MAX_CHARS": 280,
+  "CHECKPOINT_INTERVAL": 200,
+  "REPORT_EVERY_S": 30,
+  "OMNI_STEPS": 20,
+  "OMNI_GUIDANCE": 2.0,
+  "OMNI_SPEED": 1.0,
+  "OMNIVOICE_PRECISION": "f16",
+  "TTS_BACKEND": "cuda",
+  "TEXT_STAGE_MODE": "continuous",
+  "INITIAL_TEXT_BUFFER": 128,
+  "LLM_BUFFER_TARGET": 512,
+  "LLM_GPU": null,
+  "MAX_JOB_RETRIES": 3,
+  "MAX_AUDIO_SECONDS": 45.0,
+  "MIN_AUDIO_SECONDS": 0.6,
+  "MIN_CPS": 4.0,
+  "MAX_CPS": 40.0,
+  "PRUNE_INVALID": true,
+  "RETRY_FAILED_ON_RESTART": false,
+  "CONTROL_TAG_RATE": 0.35,
+  "PRONUNCIATION_RATE": 0.25,
+  "MAX_PRON_PER_TEXT": 2,
+  "runtime_url": "https://github.com/0xShug0/audio.cpp/releases/download/v0.9.1/audio-v0.9.1-bin-ubuntu-x64-cuda12.8-colab.tar.gz",
+  "resolved_sample_rate": 24000,
+  "voice_route": "voice_ref",
+  "per_instance": [
+    {
+      "instance": 0,
+      "gpu": 0,
+      "clips": 5,
+      "audio_h": 0.0089,
+      "mem_saver": false,
+      "measured_vram_mb": 2571,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.24
+    },
+    {
+      "instance": 1,
+      "gpu": 1,
+      "clips": 4,
+      "audio_h": 0.0094,
+      "mem_saver": false,
+      "measured_vram_mb": 2571,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.27
+    },
+    {
+      "instance": 2,
+      "gpu": 0,
+      "clips": 4,
+      "audio_h": 0.0087,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.25
+    },
+    {
+      "instance": 3,
+      "gpu": 1,
+      "clips": 5,
+      "audio_h": 0.0087,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.24
+    },
+    {
+      "instance": 4,
+      "gpu": 0,
+      "clips": 4,
+      "audio_h": 0.006,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.19
+    },
+    {
+      "instance": 5,
+      "gpu": 1,
+      "clips": 5,
+      "audio_h": 0.0072,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.2
+    },
+    {
+      "instance": 6,
+      "gpu": 0,
+      "clips": 5,
+      "audio_h": 0.0072,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.19
+    },
+    {
+      "instance": 7,
+      "gpu": 1,
+      "clips": 4,
+      "audio_h": 0.0066,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.21
+    },
+    {
+      "instance": 8,
+      "gpu": 0,
+      "clips": 4,
+      "audio_h": 0.0053,
+      "mem_saver": false,
+      "measured_vram_mb": 2568,
+      "oom_events": 0,
+      "restarts": 0,
+      "busy_x_realtime": 0.17
+    }
+  ],
+  "llm": "Qwen/Qwen2.5-0.5B-Instruct",
+  "generated_utc": "2026-10-09T06:35:48Z",
+  "validation": {
+    "records": 40,
+    "valid": 40,
+    "invalid": 0,
+    "orphan_audio_files": 0,
+    "total_hours_valid": 0.068,
+    "avg_duration_s": 6.123,
+    "sample_rates": [
+      24000
+    ],
+    "invalid_reasons": {},
+    "clips_with_tags": 14,
+    "clips_with_pron_overrides": 10,
+    "tag_counts": {
+      "[confirmation-en]": 3,
+      "[dissatisfaction-hnn]": 2,
+      "[laughter]": 3,
+      "[sigh]": 2,
+      "[surprise-yo]": 1,
+      "[question-en]": 1,
+      "[question-oh]": 1,
+      "[surprise-wa]": 1
+    }
+  }
+}