explaingit

mozilla/deepspeech

★ 26,754C++Audience · developerComplexity · 4/5LicenseSetup · hard

TLDR

DeepSpeech was Mozilla's open-source offline speech-to-text engine that ran entirely on-device, even on a Raspberry Pi, but is now discontinued and no longer maintained.

Mindmap

mindmap
  root((DeepSpeech))
    What it does
      Speech to text
      Runs fully offline
      On-device only
    Hardware
      Raspberry Pi
      GPU servers
      CPU support
    Status
      Discontinued
      Mozilla project
      Models still available
    Audience
      Researchers
      Embedded devs
      Privacy builders
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

Things people build with this

USE CASE 1

Build an offline voice transcription tool that converts speech to text without sending audio to the cloud

USE CASE 2

Add voice command recognition to a Raspberry Pi project like a local smart home assistant

USE CASE 3

Transcribe audio files in bulk on a GPU server without per-call API costs

Tech stack

C++PythonTensorFlow

Getting it running

Difficulty · hard Time to first run · 1h+

Project is discontinued with no new releases, use only if building on existing codebase, Whisper from OpenAI is the recommended modern alternative.

Mozilla Public License 2.0, free to use and modify, changes to existing files must remain under the same license, but you can combine it with proprietary code.

In plain English

DeepSpeech was Mozilla's open-source speech-to-text engine, software that listens to audio and converts spoken words into written text, entirely on-device without sending anything to the cloud. It was designed to run offline, which made it attractive for privacy-sensitive applications or situations where internet access wasn't available. A key technical achievement was its ability to run on low-power hardware: it could transcribe speech in real time on a Raspberry Pi (a credit-card-sized computer costing around $35), as well as on more powerful GPU servers. This range made it useful for everything from embedded smart home devices to large-scale transcription pipelines. Note: this project has been discontinued by Mozilla and is no longer actively maintained. For developers looking for a similar capability today, Mozilla's work here influenced several successor projects, and alternatives like Whisper (from OpenAI) have largely taken over this space. The code and pre-trained models remain available for historical reference or for projects that need to build on the existing foundation, but you should not start a new project expecting ongoing updates or support.

Copy-paste prompts

Prompt 1
How do I use the DeepSpeech Python package to transcribe a WAV audio file entirely offline?
Prompt 2
Show me how to set up DeepSpeech on a Raspberry Pi 4 to recognize simple voice commands in real time
Prompt 3
How do I load a pre-trained DeepSpeech model and stream audio from a microphone for live transcription?
Prompt 4
What are the best modern alternatives to DeepSpeech for offline speech recognition now that the project is discontinued?
Open on GitHub → Explain another repo

← mozilla on gitmyhub — every repo by this author, as a profile.

Verify against the repo before relying on details.