Request access to moore-tts-spark
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
This model is part of a research benchmark on text-to-speech for Mooré. Requests are reviewed by hand, usually within a few days. Generated speech can imitate real voices, so access comes with a few conditions: respect the license (CC BY-NC-SA 4.0), do not clone or imitate a real person's voice without their consent, say clearly that the audio is synthetic when you share it, and do not use the model for fraud, harassment, impersonation or political misinformation.
Log in or Sign Up to review the conditions and access this model content.
Mooré Spark-TTS (fine-tuned)
SparkAudio/Spark-TTS-0.5B with its language model fully fine-tuned on 54.6 hours of read Mooré. It clones a voice from the BiCodec global tokens of a short reference clip.
- CER 1.29 % on 150 held-out Bible verses, against 0.47 % for the real recordings and 58.12 % for the untouched base model
- Zero-shot voice cloning from a reference clip, 16 kHz output, real-time factor 0.27 on one RTX 5090 (one verse at a time)
- Part of a controlled benchmark of open TTS architectures on Mooré (same data, same splits, same evaluation)
Samples
Four verses drawn at random from the held-out dev set (chapters never seen in training). For each one: this model, the untouched base model, and the reference clip of the voice being cloned.
| Text | Voice | Type | Audio |
|---|---|---|---|
| Mam sã n zẽk m zugu, yãmb tãoosda maam wa gɩgemd sẽn digd bũmbu, la y le tar y pãngã n maand maam wẽnga. | V13 | this model (CER 0.0%) | |
| Mam sã n zẽk m zugu, yãmb tãoosda maam wa gɩgemd sẽn digd bũmbu, la y le tar y pãngã n maand maam wẽnga. | V13 | SparkAudio/Spark-TTS-0.5B, no fine-tuning (CER 60.4%) | |
| (voice prompt: a different verse by the same reader) | V13 | reference clip | |
| T'a Zeezi yeel-a: Mam sẽn gomd ne foomã, mam yaa yẽnda. | V04 | this model (CER 0.0%) | |
| T'a Zeezi yeel-a: Mam sẽn gomd ne foomã, mam yaa yẽnda. | V04 | SparkAudio/Spark-TTS-0.5B, no fine-tuning (CER 28.8%) | |
| (voice prompt: a different verse by the same reader) | V04 | reference clip | |
| A wilga tõnd t'a yãa malɛk sẽn wa n yaas a roogẽ wã, n yeele: 'Tʋm rap Zope tɩ b tɩ bool a Sɩmo b sẽn boond me t'a Pɩyɛɛrã, | V07 | this model (CER 1.7%) | |
| A wilga tõnd t'a yãa malɛk sẽn wa n yaas a roogẽ wã, n yeele: 'Tʋm rap Zope tɩ b tɩ bool a Sɩmo b sẽn boond me t'a Pɩyɛɛrã, | V07 | SparkAudio/Spark-TTS-0.5B, no fine-tuning (CER 64.7%) | |
| (voice prompt: a different verse by the same reader) | V07 | reference clip | |
| La sapɩlmã na n sarma kãgrã, la b na n sirga tẽngã fasɩ. | V11 | this model (CER 1.9%) | |
| La sapɩlmã na n sarma kãgrã, la b na n sirga tẽngã fasɩ. | V11 | SparkAudio/Spark-TTS-0.5B, no fine-tuning (CER 46.3%) | |
| (voice prompt: a different verse by the same reader) | V11 | reference clip |
Usage
git clone https://github.com/SparkAudio/Spark-TTS && cd Spark-TTS && pip install -r requirements.txt
huggingface-cli download anyantudre/moore-tts-spark --local-dir pretrained_models/moore-spark
python -m cli.inference --model_dir pretrained_models/moore-spark --save_dir out \
--prompt_speech_path reference.wav --text "Yãmb kɩtame tɩ nintãm lebg b rɩɩbo."
Training
| Base model | SparkAudio/Spark-TTS-0.5B |
| Parameters | 0.66B (Qwen2.5-0.5B LM 507M + BiCodec 156M) |
| Output | 16000 Hz mono |
| Data | 54.6 h, 20,491 verses read by ~16 voices, jw.org Mooré Bible recordings (24 kHz), train chapters only; edge silences trimmed, loudness -20 LUFS |
- Full fine-tuning of the Qwen2.5-0.5B language model; BiCodec and wav2vec2 kept frozen and used to precompute the speech tokens
- Prompt layout identical to the upstream zero-shot prompt without prompt text (task token, text, 32 global tokens), so the official inference code works unchanged
- 4,258 steps (8 epochs), lr 1e-4 with 200 warmup steps and cosine decay, about 24k tokens per step, bf16 autocast
- One RTX 5090, 1.1 GPU-hours; snapshot chosen by CER of the eval ASR on dev150 (step 3,000)
Results
| dev150 (150 verses, 20 held-out chapters, 9 voices) | CER | WER | CER on ɛ ɩ ʋ and nasals | Speaker sim. to prompt (ECAPA) | UTMOSv2 | F0 contour dist. (st) |
|---|---|---|---|---|---|---|
| Real recordings | 0.47 % | 1.85 % | 1.32 % | 0.73 | 3.03 | 0.00 |
| SparkAudio/Spark-TTS-0.5B, no fine-tuning | 58.12 % | 94.54 % | 128.41 % | 0.44 | 2.96 | 2.53 |
| This model | 1.29 % | 4.56 % | 2.49 % | 0.68 | 3.22 | 1.60 |
CER: anyantudre/moore-asr-eval-w2vbert, greedy CTC, never trained on these chapters. Speaker similarity: cosine between ECAPA-TDNN (speechbrain/spkrec-ecapa-voxceleb) embeddings of the audio and of the voice prompt; for the real recordings it compares two different verses by the same reader, which is the ceiling. UTMOSv2 is an English-trained naturalness predictor and is only a rough guide for Mooré. F0 contour distance: word-aligned DTW between synthesized and natural pitch, in semitones (lower is closer). Every system clones the same reference clip per verse.
Limitations
- Trained on read Bible speech: the prosody sounds like Bible reading, and other domains are untested.
- Output is 16 kHz (BiCodec), lower bandwidth than the 24 kHz systems of the benchmark.
- Do not pass --prompt_text: fine-tuning used the prompt without its transcript, and the continuation mode was not trained.
License
CC BY-NC-SA 4.0, inherited from SparkAudio/Spark-TTS-0.5B. The training audio comes from Bible recordings whose terms restrict redistribution; it is not included, apart from the short reference clips in samples/.
- Downloads last month
- -
Model tree for anyantudre/moore-tts-spark
Base model
SparkAudio/Spark-TTS-0.5B