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What is speech-to-speech?

huggingface/speech-to-speech — explained in plain English

Analysis updated 2026-06-26

4,740PythonAudience · developerComplexity · 3/5Setup · moderate

In one sentence

Build a fully local AI voice assistant that listens to you, understands your speech, generates a reply with a language model, and speaks back, all running on your own machine with no paid API needed.

Mindmap

mindmap
  root((repo))
    What it does
      Local voice assistant
      Listen think speak
      No paid API needed
    Pipeline Stages
      Voice activity detection
      Speech to text
      Language model reply
      Text to speech
    Run Modes
      Local single machine
      Server and client split
      WebSocket and API mode
    Hardware
      Apple Silicon optimized
      GPU or CPU
    Models
      Swappable each stage
      Hugging Face hub
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What do people build with it?

USE CASE 1

Run a fully private voice chatbot on your own laptop that listens, thinks, and speaks back without sending data to any external service.

USE CASE 2

Split the heavy AI models onto a server and connect a lightweight client device for audio input and output.

USE CASE 3

Swap in different speech-to-text or text-to-speech models to tune speed vs quality for your hardware.

USE CASE 4

Expose the voice pipeline as a real-time WebSocket API so other apps or scripts can connect to it.

What is it built with?

PythonPyTorchHugging FaceWebSocket

How does it compare?

huggingface/speech-to-speechbing-su/adetailercharles2gan/gda-android-reversing-tool
Stars4,7404,7404,743
LanguagePythonPythonPython
Setup difficultymoderateeasymoderate
Complexity3/52/54/5
Audiencedeveloperdesignerdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 1h+

Install via pip. Base install covers the main pipeline, add optional extras for faster transcription or voice cloning. Apple Silicon users get optimised model variants out of the box.

Open source from Hugging Face, free to use and modify. No paid API required for the default setup.

So what is it?

This project lets you build a voice agent that runs entirely on your own computer using open-source AI models. You speak to it, it understands you, thinks of a response, and speaks back. No paid API is required, though you can optionally connect to one for the language model step. The pipeline has four stages that pass data from one to the next. First, voice activity detection listens to the microphone and detects when you are actually speaking. Second, a speech-to-text model transcribes your words. Third, a language model reads the transcription and generates a text reply. Fourth, a text-to-speech model turns that reply into audio you hear. Each stage is swappable: you can pick from a list of supported models for each one depending on your hardware and preference. You can run the pipeline in several modes. The local mode runs everything on one machine. The server and client mode splits the heavy models onto a server while a lightweight client handles audio. There is also a WebSocket mode and a mode that exposes a real-time API compatible with other apps. On Apple Silicon machines, several of the models have optimized versions that run much faster. Installation is through a standard Python package manager. The base install covers the most common voice-agent path, and optional extras let you add specific backends for faster transcription, voice cloning, or other features. The project comes from Hugging Face and defaults to models available on their model hub.

Copy-paste prompts

Prompt 1
Walk me through installing the Hugging Face speech-to-speech project on a MacBook with Apple Silicon and starting a basic local voice conversation.
Prompt 2
How do I swap the default speech-to-text model for a faster one in the speech-to-speech pipeline? Show me which config to change.
Prompt 3
I want to run the heavy AI models on a Linux server and connect to them from my laptop for audio. How do I set up the server-client mode in speech-to-speech?
Prompt 4
Can I use my own fine-tuned language model from Hugging Face hub in this pipeline instead of the default one? How do I point the pipeline at it?
Prompt 5
Show me how to expose the speech-to-speech pipeline as a WebSocket API so a separate web app can send audio and receive spoken replies.

Frequently asked questions

What is speech-to-speech?

Build a fully local AI voice assistant that listens to you, understands your speech, generates a reply with a language model, and speaks back, all running on your own machine with no paid API needed.

What language is speech-to-speech written in?

Mainly Python. The stack also includes Python, PyTorch, Hugging Face.

What license does speech-to-speech use?

Open source from Hugging Face, free to use and modify. No paid API required for the default setup.

How hard is speech-to-speech to set up?

Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.

Who is speech-to-speech for?

Mainly developer.

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