{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"},{"label":"Speech","url":"https://skillfed.io/packages/category/multimedia-sound-audio-speech"}],"enrichment":{"capability":"OmniVoice generates speech from text in over 600 languages using a diffusion-based model, with support for voice cloning from reference audio and voice design via speaker attributes.","skillfed_tags":["speech-synthesis","voice-cloning","multilingual"],"use_cases":["Clone a speaker's voice from a 3\u201310 second reference clip and generate speech in any of 600+ languages.","Synthesize speech with specific speaker characteristics (gender, age, pitch, accent) without reference audio.","Build multilingual voice applications with fine-grained control over pronunciation and non-verbal cues.","Integrate zero-shot TTS into production systems where low inference latency is required.","Create cross-lingual voice clones where reference and target languages differ, accepting the accent carryover."],"what_it_does":"OmniVoice is a multilingual text-to-speech model built on a diffusion language model architecture that converts text to speech across over 600 languages. It operates in three modes: zero-shot voice cloning (copying a speaker's voice from a short reference clip), voice design (synthesizing speech with specified speaker attributes like gender, age, and accent), and standard TTS. The model runs on PyTorch and depends on transformers, librosa, torchaudio, and several audio utilities to handle speech generation, audio I/O, and model inference.\n\nThe package is designed for developers and researchers who need multilingual speech synthesis with fine-grained control. It supports non-verbal symbols (e.g., [laughter]), pronunciation correction via pinyin or phonemes, and claims inference speeds as low as 0.025 RTF (40x faster than real-time). Voice clones can be saved and reused across sessions. The model automatically falls back to standard attention on unsupported hardware (e.g., XPU without flash_attn) and integrates with Whisper ASR for automatic transcription of reference audio when manual transcription is not provided.","worth_installing":"Yes, if you need multilingual TTS with voice cloning or design. The broad language coverage (600+), active maintenance, permissive license, and low install friction make it a strong choice. Requires upfront PyTorch setup and GPU memory; voice design mode is less stable outside Chinese and English. No known vulnerabilities."},"id":"omnivoice","links":{"html":"https://skillfed.io/packages/omnivoice","md":"https://skillfed.io/packages/omnivoice.md","pypi":"https://pypi.org/project/omnivoice/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-16","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"omnivoice","python_support":"supports_current","summary":"OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models"},"popularity":{"monthly_downloads":206446,"position":9573,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.1"}