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mlx-audio: High-Performance Speech Processing (TTS, STT, STS) on Apple Silicon

An efficient open-source library built on Apple MLX for accelerating Text-to-Speech, Speech-to-Text, and Speech-to-Speech tasks directly on Apple Silicon hardware.

Python
Added on 2025年5月13日
View on GitHub
mlx-audio: High-Performance Speech Processing (TTS, STT, STS) on Apple Silicon preview
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Project Introduction

Summary

mlx-audio is a specialized library built on Apple's MLX framework, offering high-performance Text-to-Speech, Speech-to-Text, and Speech-to-Speech capabilities directly on Apple Silicon devices. It aims to provide developers and researchers with an efficient tool for local speech processing tasks.

Problem Solved

Traditional speech processing libraries often lack native optimization for Apple Silicon, leading to suboptimal performance or reliance on cloud services. mlx-audio provides an efficient, on-device solution by utilizing the MLX framework.

Core Features

Text-to-Speech (TTS)

Convert text input into natural-sounding speech.

Speech-to-Text (STT)

Transcribe spoken language from audio input into text.

Speech-to-Speech (STS)

Transform speech from one form to another, such as voice conversion.

MLX-Powered Performance

Leverages Apple's MLX framework for native acceleration on Apple Silicon.

Optimized for Apple Silicon

Designed for low-latency and efficient on-device processing.

Tech Stack

MLX (Apple)
Python

Use Cases

mlx-audio is suitable for a variety of applications where efficient, on-device speech processing is required, especially on Apple Silicon hardware.

Building On-Device Voice Assistants

Details

Develop voice-controlled interfaces or assistants that process user commands locally for faster response times and offline capabilities.

User Value

Enables faster, more responsive user interactions and allows functionality in environments without internet access.

Offline Audio Transcription and Analysis

Details

Process audio recordings for transcription, analysis, or summarization directly on the device, ensuring data privacy and reducing cloud costs.

User Value

Provides privacy-preserving data processing and reduces operational costs associated with cloud-based transcription services.

Real-time Speech Transformation

Details

Implement real-time voice filters, transformations, or cloning features within applications.

User Value

Allows for creative audio manipulation and personalization features directly within applications.

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