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MLX-Audio download for Windows

Free download MLX-Audio Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named MLX-Audio whose latest release can be downloaded as v0.4.4sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named MLX-Audio with OnWorks for free.

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Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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MLX-Audio


DESCRIPTION

MLX-Audio is a speech library built on Apple’s MLX framework and optimized for Apple Silicon machines (M-series Macs). It focuses on text-to-speech and speech-to-speech workflows, with APIs and a command-line interface that make it easy to generate high-quality audio from text. Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management.



Features

  • Apple-Silicon-optimized speech library built on MLX for fast local inference
  • Command-line and Python APIs for TTS with controls for voice, speed, language, and output format
  • Web interface with live waveform and 3D audio visualization plus file upload and playback
  • Support for multi-language text-to-speech and transcription scenarios
  • Quantization options and efficient model loading for better performance on resource-limited devices
  • Built-in examples for tasks like audiobook creation and integrated FastAPI server for HTTP access


Programming Language

Python


Categories

Text to Speech, Text-to-Speech (TTS) Models

This is an application that can also be fetched from https://sourceforge.net/projects/mlx-audio.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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