tiny-voca: weights, ONNX export, phonemizer data and samples

.gitattributes

@@ -33,3 +33,11 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+samples/F2-1.wav filter=lfs diff=lfs merge=lfs -text
+samples/F2-2.wav filter=lfs diff=lfs merge=lfs -text
+samples/F2-3.wav filter=lfs diff=lfs merge=lfs -text
+samples/F2-4.wav filter=lfs diff=lfs merge=lfs -text
+samples/M2-1.wav filter=lfs diff=lfs merge=lfs -text
+samples/M2-2.wav filter=lfs diff=lfs merge=lfs -text
+samples/M2-3.wav filter=lfs diff=lfs merge=lfs -text
+samples/M2-4.wav filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,202 @@
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README.md

@@ -0,0 +1,217 @@
+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-to-speech
+tags:
+- text-to-speech
+- onnx
+datasets:
+- n4ze3m/tiny-voca
+---
+# tiny-voca
+
+tiny-voca is a small English text-to-speech model with two voices, F2 (female)
+and M2 (male). The complete model, including the waveform generator, has 4.5M
+parameters and was trained from scratch on about 18 hours of synthetic speech.
+It runs about 70x faster than real time on four CPU threads.
+
+<audio controls src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/F2-1.wav"></audio>
+
+- Code: https://github.com/n4ze3m/tiny-voca
+- Phonemizer: https://github.com/n4ze3m/dizione
+- Dataset: https://huggingface.co/datasets/n4ze3m/tiny-voca
+
+| | |
+|---|---|
+| Parameters | 4,537,291 |
+| Voices | F2, M2 (American English) |
+| Output | 24 kHz mono |
+| Input | Text, converted to phonemes with dizione |
+| Pretrained weights in the model | None |
+| License | Apache-2.0 |
+
+## Files
+
+| File | Size | Contents |
+|---|---:|---|
+| `tiny-voca.pt` | 18.2 MB | PyTorch weights, float32 |
+| `onnx/model.onnx` | 21.4 MB | ONNX export, float32, opset 17 |
+| `config.json` | | Model settings, phoneme vocabulary, voices |
+| `phonemizer/` | 5.4 MB | Data files for dizione |
+| `samples/` | | The audio on this page |
+
+SHA256:
+
+- `tiny-voca.pt`: `ebb22871524c5732520fb1652e6aefcec708a7452e83bdd00adcf6181db5ef70`
+- `onnx/model.onnx`: `fe6d918791a15b82e37465981d7f27a070e46b46635e5a3482fc8dff87a1ae46`
+
+## Samples
+
+| Text | F2 | M2 |
+|---|---|---|
+| Hello! This is tiny voca, a small text to speech model that runs on a phone or in a browser. | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/F2-1.wav"></audio> | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/M2-1.wav"></audio> |
+| The meeting moved to 3:30 pm on March 14th, so we have about 45 minutes left. | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/F2-2.wav"></audio> | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/M2-2.wav"></audio> |
+| Did you really think I would forget your birthday? | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/F2-3.wav"></audio> | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/M2-3.wav"></audio> |
+| She had never seen the sea before, and for a long while she stood at the edge of the water without saying a word. | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/F2-4.wav"></audio> | <audio controls preload="none" src="https://huggingface.co/n4ze3m/tiny-voca/resolve/main/samples/M2-4.wav"></audio> |
+
+## Usage
+
+### PyTorch
+
+```bash
+pip install git+https://github.com/n4ze3m/dizione git+https://github.com/n4ze3m/tiny-voca
+hf download n4ze3m/tiny-voca --local-dir tiny-voca
+export DIZIONE_DATA=tiny-voca/phonemizer
+
+python -m tiny_voca.infer \
+  --checkpoint tiny-voca/tiny-voca.pt \
+  --voice F2 \
+  --text "Hello! This is tiny voca." \
+  --output hello.wav
+```
+
+| Option | Default | Meaning |
+|---|---|---|
+| `--voice` | `F2` | `F2` or `M2` |
+| `--speed` | 1.0 | Speaking rate |
+| `--pitch-shift` | 0 | Added to log F0. 0.058 is about one semitone. |
+| `--pitch-range` | 1.0 | Scales pitch movement around the utterance mean. |
+
+### ONNX
+
+The graph takes phoneme ids and stress values and returns the waveform. Text is
+converted to ids outside the graph with dizione; the ids are the positions in
+`vocab` in `config.json`.
+
+```python
+import numpy as np
+import onnxruntime as ort
+import soundfile as sf
+import dizione   # needs DIZIONE_DATA=tiny-voca/phonemizer
+
+phones = dizione.phonemize("Hello! This is tiny voca.")
+one = lambda value: np.array([value], dtype=np.float32)
+
+session = ort.InferenceSession("tiny-voca/onnx/model.onnx")
+audio, durations = session.run(None, {
+    "tokens": np.array([phones.ids], dtype=np.int64),
+    "stress": np.array([phones.stress], dtype=np.int64),
+    "voice": np.array([0], dtype=np.int64),      # 0 = F2, 1 = M2
+    "speed": one(1.0),
+    "pitch_shift": one(0.0),
+    "pitch_range": one(1.0),
+})
+sf.write("hello.wav", audio[0], 24000)
+```
+
+| Input | Type | Shape | Meaning |
+|---|---|---|---|
+| `tokens` | int64 | [1, N] | Phoneme ids, including the start and end tokens |
+| `stress` | int64 | [1, N] | 0 none, 1 primary, 2 secondary |
+| `voice` | int64 | [1] | 0 = F2, 1 = M2 |
+| `speed` | float32 | [1] | 1.0 as predicted; larger is faster |
+| `pitch_shift` | float32 | [1] | Added to log F0 |
+| `pitch_range` | float32 | [1] | Scales pitch movement |
+
+| Output | Type | Shape | Meaning |
+|---|---|---|---|
+| `audio` | float32 | [1, samples] | Waveform at 24 kHz |
+| `durations` | int64 | [1, N] | Length of each token in frames of 256 samples |
+
+The model reads one utterance per call, up to 512 tokens and 32 seconds. Split
+longer text into sentences. The same file runs in onnxruntime-web
+(WebAssembly). Its audio matches the PyTorch model to within 0.6% of the peak
+amplitude, apart from the random noise signal, which each runtime draws itself.
+
+## Model
+
+Text is converted to phonemes with a stress value for each. A transformer
+encoder (4 blocks) reads the phonemes, a duration predictor gives each one a
+length in frames, and two frame-level transformers (2 and 5 blocks) predict
+pitch, voicing and energy and then the parameters of the waveform generator.
+All blocks use 192 channels, 4 heads and rotary position embeddings.
+
+The waveform is produced by a source-filter synthesizer instead of a neural
+vocoder. A band-limited pulse train at the predicted pitch and a noise signal
+are each shaped by a time-varying filter, whose cepstrum the network predicts
+once per frame (256 samples, 10.7 ms). This part has 25,862 parameters.
+
+| Component | Parameters |
+|---|---:|
+| Embeddings (phoneme, stress, voice) | 16,704 |
+| Text encoder | 1,588,864 |
+| Duration and pause predictor | 123,906 |
+| Frame transformer A, prosody head | 795,971 |
+| Frame transformer B | 1,985,984 |
+| Source-filter waveform head | 25,862 |
+| Total | 4,537,291 |
+
+## Training
+
+| | |
+|---|---|
+| Data | [n4ze3m/tiny-voca](https://huggingface.co/datasets/n4ze3m/tiny-voca): 16,018 clips, 17.6 hours, two voices |
+| Steps | 104,737 |
+| Hardware | One RTX 4090, 7.7 hours |
+| Losses | Multi-resolution spectral losses; adversarial loss with multi-period and multi-resolution discriminators after step 8,000 |
+
+The training audio is synthetic. Both voices were created from text
+descriptions with Qwen3-TTS VoiceDesign, and the recordings were generated with
+Qwen3-TTS 1.7B Base. No recording of a real speaker is involved. Phoneme
+durations come from forced alignment with
+`facebook/wav2vec2-lv-60-espeak-cv-ft`, which is used only to label the
+training data. No pretrained weights are part of the model.
+
+## Evaluation
+
+Word error rate of synthesized speech, transcribed with Whisper small.en. The
+recordings of the same sentences are scored the same way for reference.
+
+| Sentences | Clips | WER, tiny-voca | WER, recordings |
+|---|---:|---:|---:|
+| Validation | 8 | 0.6% | 0.6% |
+| Test | 8 | 0.9% | 0.9% |
+| New sentences, not in the dataset | 16 | 0.0% | |
+
+These sets are small and the scores are a sanity check, not a benchmark. No
+formal listening test has been run.
+
+## Limitations
+
+- English only, two fixed voices, no voice cloning.
+- The voice is clear but can sound slightly synthetic.
+- The same text is always read the same way. There is no sampling of prosody.
+- Speech is slightly faster than the training recordings at the default speed.
+- Foreign names and unusual spellings are often mispronounced. Numbers,
+  abbreviations and homographs depend on the phonemizer.
+- No streaming.
+- The training data is itself synthetic, so the model cannot be more natural
+  than the model that generated it.
+
+## License
+
+The weights and code are released under Apache-2.0. The files in `phonemizer/`
+are derived from the CMU Pronouncing Dictionary and other sources; their
+licenses are in `phonemizer/LICENSE.cmudict` and
+`phonemizer/LICENSE.homograph-data`.
+
+## Citation
+
+```bibtex
+@software{nazeem2026tinyvoca,
+  author = {Nazeem, Muhammed},
+  title  = {tiny-voca: a 4.5M-parameter two-voice English text-to-speech model},
+  year   = {2026},
+  url    = {https://huggingface.co/n4ze3m/tiny-voca}
+}
+```
+
+Author: Muhammed Nazeem ([ORCID 0009-0002-9991-0217](https://orcid.org/0009-0002-9991-0217)).
+
+## Acknowledgements
+
+The design builds on FastSpeech 2 (explicit duration and prosody prediction),
+DDSP and the neural homomorphic vocoder (source-filter synthesis with predicted
+filters), and HiFi-GAN and UnivNet (discriminators). No code or weights from
+these projects are used.

config.json

@@ -0,0 +1,149 @@
+{
+ "model": {
+  "sample_rate": 24000,
+  "hop": 256,
+  "n_fft": 1024,
+  "n_mels": 80,
+  "f0_min": 50.0,
+  "f0_max": 600.0,
+  "speakers": [
+   "F2",
+   "M2"
+  ],
+  "vocab_size": 76,
+  "channels": 192,
+  "heads": 4,
+  "feedforward": 640,
+  "kernel": 7,
+  "encoder_layers": 4,
+  "prosody_layers": 2,
+  "acoustic_layers": 5,
+  "dropout": 0.1,
+  "predictor_channels": 128,
+  "synth_fft": 512,
+  "synth_hop": 128,
+  "noise_fft": 256,
+  "noise_hop": 64,
+  "cep_causal": 80,
+  "cep_anti": 16,
+  "noise_cep": 32,
+  "harmonic_limit": 0.47,
+  "max_tokens": 512,
+  "max_frames": 3000,
+  "mel_mean": -5.0,
+  "mel_scale": 5.0,
+  "energy_mean": -4.0,
+  "energy_scale": 2.0,
+  "pitch_reference_hz": 200.0
+ },
+ "step": 104737,
+ "sample_rate": 24000,
+ "hop": 256,
+ "voices": [
+  "F2",
+  "M2"
+ ],
+ "phonemizer": {
+  "name": "dizione",
+  "version": 4,
+  "fingerprint": "c729f235e10daa1a08ce7711169c1cb93fb552b3c24eecb16527513d7b69d4da"
+ },
+ "stress": {
+  "none": 0,
+  "primary": 1,
+  "secondary": 2
+ },
+ "onnx": {
+  "file": "onnx/model.onnx",
+  "inputs": [
+   "tokens",
+   "stress",
+   "voice",
+   "speed",
+   "pitch_shift",
+   "pitch_range"
+  ],
+  "outputs": [
+   "audio",
+   "durations"
+  ]
+ },
+ "vocab": {
+  "<pad>": 0,
+  "<bos>": 1,
+  "<eos>": 2,
+  "<sp>": 3,
+  "<unk>": 4,
+  ",": 5,
+  ".": 6,
+  "?": 7,
+  "!": 8,
+  ";": 9,
+  ":": 10,
+  "\"": 11,
+  "'": 12,
+  "(": 13,
+  ")": 14,
+  "—": 15,
+  "…": 16,
+  "p": 17,
+  "b": 18,
+  "t": 19,
+  "d": 20,
+  "k": 21,
+  "ɡ": 22,
+  "f": 23,
+  "v": 24,
+  "θ": 25,
+  "ð": 26,
+  "s": 27,
+  "z": 28,
+  "ʃ": 29,
+  "ʒ": 30,
+  "h": 31,
+  "m": 32,
+  "n": 33,
+  "ŋ": 34,
+  "l": 35,
+  "ɹ": 36,
+  "j": 37,
+  "w": 38,
+  "tʃ": 39,
+  "dʒ": 40,
+  "ɾ": 41,
+  "ʔ": 42,
+  "ə": 43,
+  "ɐ": 44,
+  "ɚ": 45,
+  "ᵻ": 46,
+  "ɪ": 47,
+  "i": 48,
+  "iː": 49,
+  "ɛ": 50,
+  "æ": 51,
+  "ʌ": 52,
+  "ɑː": 53,
+  "ɔ": 54,
+  "ɔː": 55,
+  "ʊ": 56,
+  "uː": 57,
+  "ɜː": 58,
+  "eɪ": 59,
+  "aɪ": 60,
+  "ɔɪ": 61,
+  "oʊ": 62,
+  "aʊ": 63,
+  "iə": 64,
+  "oː": 65,
+  "ɑːɹ": 66,
+  "ɔːɹ": 67,
+  "oːɹ": 68,
+  "ɪɹ": 69,
+  "ɛɹ": 70,
+  "ʊɹ": 71,
+  "aɪɚ": 72,
+  "aɪə": 73,
+  "əl": 74,
+  "n̩": 75
+ }
+}

onnx/model.onnx

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phonemizer/LICENSE.cmudict

@@ -0,0 +1,33 @@
+Copyright (C) 1993-2015 Carnegie Mellon University. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions
+are met:
+
+1. Redistributions of source code must retain the above copyright
+   notice, this list of conditions and the following disclaimer.
+   The contents of this file are deemed to be source code.
+
+2. Redistributions in binary form must reproduce the above copyright
+   notice, this list of conditions and the following disclaimer in
+   the documentation and/or other materials provided with the
+   distribution.
+
+This work was supported in part by funding from the Defense Advanced
+Research Projects Agency, the Office of Naval Research and the National
+Science Foundation of the United States of America, and by member
+companies of the Carnegie Mellon Sphinx Speech Consortium. We acknowledge
+the contributions of many volunteers to the expansion and improvement of
+this dictionary.
+
+THIS SOFTWARE IS PROVIDED BY CARNEGIE MELLON UNIVERSITY ``AS IS'' AND
+ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL CARNEGIE MELLON UNIVERSITY
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+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

phonemizer/LICENSE.homograph-data

@@ -0,0 +1,202 @@
+
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phonemizer/align.json

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phonemizer/g2p.json

@@ -0,0 +1,83 @@
+{
+ "letters": "abcdefghijklmnopqrstuvwxyz'",
+ "symbols": [
+  "AA0",
+  "AA1",
+  "AA2",
+  "AE0",
+  "AE1",
+  "AE2",
+  "AH0",
+  "AH1",
+  "AH2",
+  "AO0",
+  "AO1",
+  "AO2",
+  "AW0",
+  "AW1",
+  "AW2",
+  "AY0",
+  "AY1",
+  "AY2",
+  "B",
+  "CH",
+  "D",
+  "DH",
+  "EH0",
+  "EH1",
+  "EH2",
+  "ER0",
+  "ER1",
+  "ER2",
+  "EY0",
+  "EY1",
+  "EY2",
+  "F",
+  "G",
+  "HH",
+  "IH0",
+  "IH1",
+  "IH2",
+  "IY0",
+  "IY1",
+  "IY2",
+  "JH",
+  "K",
+  "L",
+  "M",
+  "N",
+  "NG",
+  "OW0",
+  "OW1",
+  "OW2",
+  "OY0",
+  "OY1",
+  "OY2",
+  "P",
+  "R",
+  "S",
+  "SH",
+  "T",
+  "TH",
+  "UH0",
+  "UH1",
+  "UH2",
+  "UW0",
+  "UW1",
+  "UW2",
+  "V",
+  "W",
+  "Y",
+  "Z",
+  "ZH"
+ ],
+ "width": 64,
+ "hidden": 127,
+ "convs": 0,
+ "kernel": 3,
+ "layers": 2,
+ "slots": 2,
+ "parameters": 458682,
+ "test_word_error": 0.3239775461106656,
+ "test_phoneme_error": 0.07940553088413403
+}

phonemizer/g2p.npz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:eb3fd519ff00e72d850928d2fccb968adc36134bca2f3bda09de7e794c2ed01b
+size 1840104

phonemizer/homographs.json

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