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Navoiy Tts

Lison Navoiy TTS is Aisha's public Uzbek expressive text-to-speech model artifact built on CosyVoice2.

ArtOtherBasismodellFunAudioLLM/CosyVoice2-0.5BVersionRevision 7060e5eBBewertung

Modellquelle

Art
Other
Dateigröße
1,88 GB
Basismodell
FunAudioLLM/CosyVoice2-0.5B
Version
vRevision 7060e5e
Aktualisiert
19. Okt. 2026
Downloads
0
Quelle
Hugging Face

Quellenbeschreibung

Lison Navoiy TTS

Lison Navoiy TTS is Aisha's public Uzbek expressive text-to-speech model artifact built on CosyVoice2.

This repository contains the LLM/checkpoint component and demo assets. It is not a standalone one-file inference package; inference requires the upstream CosyVoice/CosyVoice2 runtime and compatible base model assets.

Model summary

FieldValue
Product familyLison
TaskUzbek text-to-speech
Base modelFunAudioLLM/CosyVoice2-0.5B
LanguageUzbek (uz)
LicenseApache-2.0
Main checkpointemotion_600h_joint.pt
Repository visibilitypublic
Revision912e6bb6663f11e5dec5de830ca06ea8dd4c985f

Intended use

  • Uzbek expressive TTS research and demos
  • Voice-agent speech generation experiments
  • CosyVoice2-based Lison model evaluation

Files

FileSize
emotion_600h_joint.pt1.88 GiB
demo/long_form.wav0.49 MiB
demo/numbers_dates.wav0.42 MiB
demo/happy.wav0.24 MiB
demo/calm_intro.wav0.23 MiB
demo/angry.wav0.23 MiB
demo/sad.wav0.22 MiB
demo/warm_agent.wav0.17 MiB
demo/surprised.wav0.16 MiB
LICENSE0.01 MiB

Demo assets

The demo/ folder contains generated Uzbek WAV examples and a demo manifest. Use these for quick qualitative checks, not as a replacement for systematic MOS or production latency evaluation.

Limitations

  • Requires CosyVoice/CosyVoice2 serving code and compatible dependencies.
  • Production quality depends on prompt/reference audio, normalization, serving latency, and post-processing.
  • Do not treat demo outputs as full benchmark coverage.

Related Lison datasets

  • Canonical non-emotion corpus: aisha-org/uzbek-tts-corpus-v1
  • Separate emotion dataset: aisha-org/uzbek-emotion-tts

Quellen

1 Quelle
Hugging FacePrimärVersion 7060e5e784b669e8581fbd13898a01294da7c263
huggingface.co/aisha-org/navoiy-tts/tree/7060e5e784b669e8581fbd13898a01294da7c263

Verifiziert 19. Okt.

Modellartefakte

1 Artefakt

emotion_600h_joint.pt

pt · 1,88 GB · SHA-256 ced40fe65cf0…58af · Hugging Face

Download file

Quellenauszüge

3 Auszüge

--- language: - uz license: apache-2.0 base_model: FunAudioLLM/CosyVoice2-0.5B pipeline_tag: text-to-speech tags: - lison - cosyvoice2 - uzbek - speech-synthesis - expressive-tts - voice-cloning - text-to-speech --- # Lison Navoiy TTS Lison Navoiy TTS is Aisha's public Uzbek expressive text-to-speech model artifact built on CosyVoice2. This repository contains the LLM/checkpoint component and demo assets. It is not a standalone one-file inference package; inference requires the upstream CosyVoice/CosyVoice2 runtime and compatible base model assets. ## Model summary | Field | Value | | --- | --- | | Product family | Lison | | Task | Uzbek text-to-speech | | Base model | `FunAudioLLM/CosyVoice2-0.5B` | | Language | Uzbek (`uz`) | | License | Apache-2.0 | | Main checkpoint | `emotion_600h_joint.pt` | | Repository visibility | public | | Revision | `912e6bb6663f11e5dec5de830ca06ea8dd4c985f` | ## Intended use - Uzbek expressive TTS research and demos - Voice-agent speech generation experiments - CosyVoice2-based Lison model evaluation ## Files | File | Size | | --- | ---: | | `emotion_600h_joint.pt` | 1.88 GiB | | `demo/long_form.wav` | 0.49 MiB | | `demo/numbers_dates.wav` | 0.42 MiB | | `demo/happy.wav` | 0.24 MiB | | `demo/calm_intro.wav` | 0.23 MiB | | `demo/angry.wav` | 0.23 MiB | | `demo/sad.wav` | 0.22 MiB | | `demo/warm_agent.wav` | 0.17 MiB | | `demo/surprised.wav` | 0.16 MiB | | `LICENSE` | 0.01 MiB | ## Demo assets The `demo/` folder contains generated Uzbek WAV examples and a demo manifest. Use these for quick qualitative checks, not as a replacement for systematic MOS or production latency evaluation. ## Limitations - Requires CosyVoice/CosyVoice2 serving code and compatible dependencies. - Production quality depends on prompt/reference audio, normalization, serving latency, and post-processing. - Do not treat demo outputs as full benchmark coverage. ## Related Lison datasets - Canonical non-emotion corpus: `aisha-org/uzbek-tts-corpus-v1` - Separate emotion dataset: `aisha-org/uzbek-emotion-tts`

Source context: 0 downloads · 9 likes · Pipeline text-to-speech · Repo aisha-org/navoiy-tts

Source context: 0 downloads · 4 likes · Pipeline text-to-speech · Repo aisha-org/navoiy-tts