Blaizzy/mlx-audio Alternatives

Choose when you need cross-platform on-device speech processing with onnxruntime support and no Apple requirement.

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages

Choose when you need very low-latency speech for voice agents and can use non-MLX runtime.

Very low latency speech to text, intent recognition, and text to speech, for building voice agents and interfaces

Choose when you need a full speech toolkit with ASR and TTS that is cross-platform and production-oriented.

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

Choose when you need a flexible PyTorch speech toolkit for research/production with recipes for TTS and STT.

A PyTorch-based Speech Toolkit

Choose when you need an end-to-end speech processing toolkit supporting ASR/TTS with extensive recipes.

End-to-End Speech Processing Toolkit

Choose when you need a production-ready multilingual TTS with full training/deployment and don't require MLX/Apple Silicon.

Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.

Choose when you need TTS without requiring Apple Silicon/MLX and prefer a lightweight inference-only model.

Spark-TTS Inference Code

Choose when you need voice cloning for 600+ languages and prefer a non-MLX framework.

High-Quality Voice Cloning TTS for 600+ Languages

Choose when you need expressive open-weight TTS and are not tied to MLX/Apple.

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.

Choose when you need few-shot voice cloning with minimal data and a non-MLX pipeline.

1 min voice data can also be used to train a good TTS model! (few shot voice cloning)

Choose when you need tokenizer-free multilingual TTS and are outside the Apple ecosystem.

VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning

Choose when you need industrial-grade zero-shot TTS that runs on standard PyTorch.

An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System

Choose when you need cross-platform instant voice cloning without MLX.

Instant voice cloning by MIT and MyShell. Audio foundation model.

Choose when you want a PyTorch TTS with strong expressiveness rather than MLX-specific inference.

SoTA open-source TTS

Choose when you need a TTS built on Whisper-style embeddings and prefer PyTorch.

An Open Source text-to-speech system built by inverting Whisper.

Choose when you need a tiny CPU-friendly TTS and don't need Apple-specific acceleration.

A TTS that fits in your CPU (and pocket)

Choose when you need emotion-controllable TTS and want a plain PyTorch implementation.

EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine

Choose when you need only speech-to-text and want a highly optimized C++ implementation that runs on many platforms.

Port of OpenAI's Whisper model in C/C++

Choose when you need a mature PyTorch TTS toolkit with many voices and can accept an unmaintained codebase.

🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

Choose when you need only speech recognition with streaming/VAD/punctuation and prefer a non-MLX toolkit.

Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.

Choose when you need only offline speech recognition for mobile/embedded without MLX.

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

Choose when you need a state-of-the-art TTS from Qwen with voice cloning and streaming, running outside MLX.

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.

Choose when you want a zero-model cloud TTS with no local resources, at the cost of network dependency.

Use Microsoft Edge's online text-to-speech service from Python WITHOUT needing Microsoft Edge or Windows or an API key

Choose when you need a fast local neural TTS on modest hardware and can use a C++ pipeline (archived).

A fast, local neural text to speech system

Choose when you need a research toolkit for audio/music/speech generation and want PyTorch flexibility.

Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.