| # tiny-voca annotations v3: phoneme tokens and validated durations |
|
|
| Annotation layer for the recordings in this dataset at revision |
| `93dfa15bf40ec278a3ea1b418294c5620d850a8f`. It adds, for every accepted |
| recording, the phoneme token sequence and the number of acoustic frames each |
| token lasts. The audio shards are untouched; nothing here replaces them. |
|
|
| Annotation fingerprint: `ebed758f71eb2af6d241a1badd9ee951ceb05e7605ad719507d77468a6341bdd` |
| (training checkpoints record it and refuse manifests from another run). |
|
|
| ## What was wrong before |
|
|
| * The old front end piped text to `espeak-ng --stdin` without a final newline. |
| eSpeak NG 1.51 then drops the last character of the input, so the last |
| phonemes of every clause were wrong ("lips" became `l ɪ p`, "forever" became |
| `f ɔː ɹ v`). 294 of 300 sampled rows were affected. |
| * Tokens were the UTF-8 bytes of the IPA string: 2.5 byte tokens per phoneme, |
| 3.3 frames per token, and each byte (including stress marks, length marks and |
| spaces) had to own at least one frame. |
| * Durations came from a learned aligner that collapsed in all three attempts. |
|
|
| ## How these annotations were made |
|
|
| 1. **Text to phonemes.** eSpeak NG 1.51, voice `en-us`, `--ipa --sep=_`, input |
| terminated by a newline. One token per eSpeak phoneme (59 phones), stress as |
| a separate 0/1/2 feature, explicit tokens for utterance edges, word |
| boundaries and punctuation. 76 symbols in total; no unknown phoneme occurs |
| in the corpus. |
| 2. **Forced alignment.** A pretrained phoneme recogniser, |
| `facebook/wav2vec2-lv-60-espeak-cv-ft` (revision |
| `ae45363bf3413b374fecd9dc8bc1df0e24c3b7f4`, Apache-2.0), aligned each phoneme |
| sequence to its recording with CTC Viterbi. **It was used only to annotate |
| this data. None of its weights or outputs are part of the TTS model.** Its |
| label inventory is the same eSpeak phoneme set, so one aligned label is one |
| token. |
| 3. **Boundaries.** This recogniser emits each label at the start of the phone. |
| Measured against the pitch tracker's voicing flips on 300 recordings, a |
| phone starts 19 ms before the start of its first emission frame (both |
| voices). A phone lasts from its onset to the next phone's onset. |
| 4. **Pauses.** Silence (frame level below the recording's loud level minus |
| 45 dB) between two phones is given to the pause-capable token there: BOS, |
| EOS, punctuation, or the word boundary. At least 75 ms of silence is needed, |
| otherwise the gap stays with the phones (stop closures). |
| 5. **Frame grid.** Durations are counted in 256-sample frames at 24 kHz, frame |
| `i` centred on sample `i * 256`, the same grid as the stored mel and pitch |
| features. They sum to the frame count exactly and every phoneme has at least |
| one frame. |
|
|
| A second pass that re-timed boundaries with a small classifier trained from |
| scratch on these labels was evaluated (`refined-1`, `refined-2`). It did not |
| improve the timing probe below, so it is **not** used. The files are kept for |
| reference. |
|
|
| ## Quality checks |
|
|
| | Split | Accepted | Rejected | Hours accepted | |
| |---|---:|---:|---:| |
| | train | 8,186 | 40 | 10.02 | |
| | validation | 714 | 4 | 0.74 | |
| | test | 590 | 6 | 0.70 | |
|
|
| Rejected rows are listed with reasons in `<split>.rejected.jsonl`: 30 where the |
| pitch tracker found voicing in under half of the vowel frames (creaky or |
| breathy recordings), 19 with more than a quarter of phonemes weakly matched and |
| 2 with low mean confidence. The weak matches are mostly numbers that eSpeak and |
| the teacher TTS read differently ("1-800-555-0147", "In 1681", "12/09/2026"). |
| Sentence-level split isolation is unchanged: no text occurs in two splits. |
|
|
| Label-free timing probe over all accepted rows: at vowel to voiceless-consonant |
| and voiceless-fricative to vowel boundaries the voicing must flip. |
|
|
| | Voice | Boundary type | Boundaries | Flip within 1 frame (10.7 ms) | within 2 frames | |
| |---|---|---:|---:|---:| |
| | F2 | vowel to voiceless | 29,597 | 63.8% | 85.6% | |
| | F2 | fricative to vowel | 10,625 | 66.3% | 89.0% | |
| | M2 | vowel to voiceless | 29,617 | 58.0% | 81.2% | |
| | M2 | fricative to vowel | 10,685 | 65.9% | 85.6% | |
|
|
| The probe includes the pitch tracker's own jitter, so these are lower bounds on |
| boundary accuracy, not a comparison with hand labels (there are none). |
|
|
| Other statistics (`summary.json` has all of them, per voice and per phoneme): |
| mean phone length 7.5 frames (F2) and 7.0 frames (M2); 0.2% of phones last one |
| frame (97 to 99% did in the collapsed runs); a word boundary carries a pause in |
| 0.8% of cases, a comma in 47%, a semicolon in 76%. |
|
|
| ## Files |
|
|
| | File | Content | |
| |---|---| |
| | `train.jsonl`, `validation.jsonl`, `test.jsonl` | accepted rows: `id`, `speaker`, `text`, `symbols`, `tokens`, `stress`, `durations`, `frames`, `qc`, `provenance`, fingerprints | |
| | `*.rejected.jsonl` | rejected rows with reasons | |
| | `annotations.json` | identity of this run (front end, aligner revision, settings, source hashes), completion flag | |
| | `summary.json` | QC quantiles, timing probe, duration tables | |
| | `phonemes.jsonl` | front-end output per distinct text | |
| | `raw/` | per-recording alignment journal (resumable) | |
| | `refined-1/`, `refined-2/` | the evaluated, unused refinement passes | |
|
|
| `path` in a row is relative to the acoustic feature directory on the training |
| machine. Provenance fields (`text_id`, `origin`, `source_id`, `source_license`, |
| `source_url`, `teacher_model`, `reference_audio`) are copied from the source |
| rows; the dataset's `LICENSE.md` continues to apply. |
|
|
| ## Limits |
|
|
| * No hand-labelled boundaries exist for this corpus; accuracy is estimated from |
| the voicing probe and from whether a TTS model trained on these durations |
| speaks intelligibly. |
| * A pause inside an eSpeak word group has no token and stays with a phone. |
| * Where eSpeak and the teacher TTS pronounce a word differently (heteronyms, |
| some numbers), the token is eSpeak's and the audio is the teacher's. |
|
|
| Reproduce on the training machine: |
|
|
| ```bash |
| python -m tiny_voca.annotate --features <acoustic feature dir> \ |
| --output <new directory> --dataset-revision 93dfa15bf40ec278a3ea1b418294c5620d850a8f |
| ``` |
|
|
