index-tts/index-ttsGitHub
calls IMS-Toucan “choose for controllable TTS supporting over 7000 languages.”
An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
23.4kPythonactive
DigitalPhonetics/IMS-Toucan Alternatives
IMS-Toucan is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
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Listed as an alternative to
These projects were analysed and named IMS-Toucan among their alternatives. The relationship is not symmetric — how IMS-Toucan rates them is a separate judgement, made when IMS-Toucan is analysed in its own right.
QwenLM/Qwen3-TTSGitHub
calls IMS-Toucan “Choose when you need controllable TTS for over 7000 languages in a lightweight system.”
Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
13.5kPythonslowing
myshell-ai/OpenVoiceGitHub
calls IMS-Toucan “choose when you need a controllable TTS for 7000+ languages and are willing to train per speaker.”
Instant voice cloning by MIT and MyShell. Audio foundation model.
37.2kPythonslowing
QwenAudio/CosyVoiceGitHub
calls IMS-Toucan “Choose when you need controllable TTS covering 7000+ languages and fine-grained prosody control, not zero-shot voice cloning.”
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
23.1kPythonactive
SparkAudio/Spark-TTSGitHub
calls IMS-Toucan “choose for controllable TTS covering over 7000 languages.”
Spark-TTS Inference Code
11.0kPythonslowing
k2-fsa/OmniVoiceGitHub
calls IMS-Toucan “Use for a controllable TTS toolkit covering 7000+ languages, though not zero-shot-focused.”
High-Quality Voice Cloning TTS for 600+ Languages
9.3kPythonactive
jasonppy/VoiceCraftGitHub
calls IMS-Toucan “choose for highly controllable TTS with broad language coverage, if you don't need zero-shot cloning or editing.”
Zero-Shot Speech Editing and Text-to-Speech in the Wild
8.6kJupyter Notebookactive
stepfun-ai/Step-Audio-EditXGitHub
calls IMS-Toucan “Choose for controllable fast TTS across many languages if speed and language breadth matter more than editing.”
A powerful 3B-parameter, LLM-based Reinforcement Learning audio edit model excels at editing emotion, speaking style, and paralinguistics, and features robust zero-shot text-to-speech
977Pythonactive
Zyphra/ZonosGitHub
calls IMS-Toucan “choose over Zonos if you are a researcher needing trainable controllable TTS for low-resource languages; it is a narrower/older-generation academic toolkit, not an expressive zero-shot model.”
Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers.
7.2kPythondormant