| --- |
| license: other |
| license_name: bilibili-model-use-license |
| license_link: https://huggingface.co/IndexTeam/IndexTTS-2.5/blob/main/LICENSE |
| language: |
| - am |
| - om |
| - ti |
| tags: |
| - text-to-speech |
| - amharic |
| - afaan-oromoo |
| - tigrinya |
| - ethiopia |
| - voice-cloning |
| - emotional-speech |
| - lab.et |
| - azemari |
| - indextts |
| pipeline_tag: text-to-speech |
| --- |
| |
| # Azemari — Ethiopian Multilingual Voice (TTS) |
|
|
| **146 language tokens · 4 languages · 8 emotions · voice cloning · built in Addis Ababa** |
|
|
| [lab.et](https://lab.et) · [voice.et](https://voice.et) · [yakal.et](https://yakal.et) |
|
|
| --- |
|
|
| ## What is Azemari? |
|
|
| Named after the **Azemari** — Ethiopia's traditional improvising singer who can take any voice and any mood — Azemari is a fine-tuned IndexTTS-2.5 model that speaks **Amharic, Afaan Oromoo, and Tigrinya** with controlled emotion and voice cloning. |
|
|
| Built by [**lab.et**](https://lab.et), the AI lab of Ethiopia. |
|
|
| ## Capabilities |
|
|
| | Control | Token | |
| |---|---| |
| | Amharic | `<\|am\|>` | |
| | Afaan Oromoo | `<\|om\|>` | |
| | Tigrinya | `<\|ti\|>` | |
| | Shewa dialect | `<\|am\|><\|DIALECT_SHEWA\|>` | |
| | Emotion | 8-dim vector (happy, angry, sad, afraid, disgusted, melancholic, surprised, calm) | |
| | Voice | CAMPPlus speaker embedding from reference audio | |
|
|
| ## Usage |
|
|
| **Everything needed for inference is in this repository** — download it and run; no external model downloads required. |
|
|
| ```bash |
| pip install -U "huggingface_hub[cli]" |
| hf download Lab-et/azemari --local-dir azemari |
| ``` |
|
|
| 1. Set up the [IndexTTS-2.5 codebase](https://github.com/index-tts/index-tts) |
| 2. Point it at the downloaded `azemari/` directory as your checkpoint dir (it replaces the official `checkpoints/`) |
| 3. Generate. Control language with `<|am|>`, `<|om|>`, `<|ti|>` prefixes and dialects with `<|DIALECT_SHEWA|>` / `<|DIALECT_GOJJAM|>` |
|
|
| ### Repository contents |
|
|
| | File | What it is | |
| |---|---| |
| | `gpt.pth` | **Azemari** — the fine-tuned GPT (this is the model) | |
| | `config.yaml` | adapted config (60,513 text tokens, +2 language rows) | |
| | `model_v2.py`, `tokenizer_ethiopic.py` | adapted inference code + Ethiopian tokenizer | |
| | `codec.pth`, `s2mel.pth`, `feat1.pt`, `feat2.pt`, `wav2vec2bert_stats.pt` | official IndexTTS-2.5 inference components | |
| | `qwen0.6bemo4-merge/` | official emotion model | |
| | `multilingual_zh_ja_yue_char_del.tiktoken` | base tokenizer (Ethiopic special tokens extend it) | |
| | `bigvgan_generator.pth` | BigVGAN vocoder (official IndexTTS component) | |
|
|
| The only runtime fetch is the CAMPPlus speaker encoder, which the official code path loads from ModelScope (`iic/speech_campplus_sv_zh-cn_16k-common`). |
|
|
| ## Samples |
|
|
| Listen to generated samples at [Lab-et/azemari-samples](https://huggingface.co/datasets/Lab-et/azemari-samples) — emotions, voice cloning, multi-language tests. |
|
|
| ## Training |
|
|
| Fine-tuned from the [IndexTTS-2.5](https://huggingface.co/IndexTeam/IndexTTS-2.5) base checkpoint on **41,371 clips of human ground-truth Ethiopian speech** (605 hours — Amharic 61.6k, Afaan Oromoo 40.3k, Tigrinya 40.0k), with language-specific embedding rows added (109 total, +2 for OM/TI) and 5 dialect/emotion tokens extended (60,514 total, +4). |
|
|
| - Training: 58,000 steps, batch duration 1600s/update, learning rate 3.2e-3 → warmup → cosine |
| - Post-training: language/token embedding-only refinement pass (backbone frozen) |
| - Validation loss: 5.018 (step 3,000) → ~3.0 (step 58,000) |
|
|
| ## License |
|
|
| Inherited from [IndexTeam/IndexTTS-2.5](https://huggingface.co/IndexTeam/IndexTTS-2.5) — [bilibili Model Use License Agreement](https://huggingface.co/IndexTeam/IndexTTS-2.5/blob/main/LICENSE). |
|
|
| ## About lab.et |
|
|
| [**lab.et**](https://lab.et) is the AI lab of Ethiopia — building speech AI, models and infrastructure for Ethiopian languages in Addis Ababa. Our products: [voice.et](https://voice.et) (speech APIs) and [yakal.et](https://yakal.et) (the AI console, prepaid in Birr). |
|
|
| Open data: [amharic-corpus](https://huggingface.co/datasets/Lab-et/amharic-corpus) — 408.5 hours of Amharic speech. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @model{labet_azemari, |
| title = {Azemari — Ethiopian Multilingual Voice (TTS)}, |
| author = {lab.et}, |
| year = {2026}, |
| url = {https://huggingface.co/Lab-et/azemari}, |
| note = {Fine-tuned from IndexTTS-2.5} |
| } |
| ``` |
|
|
