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Tech riderRev. 5 Oct 2026

CMU Sphinx

Ch 047.3of 28 Speech Recognition Software
  1. 1Runs onAndroid, Linux, Mac, self-hosted, Windows
  2. 2CostsFree plan
  3. 3Real-time recognitionYes
  4. 4Offline recognitionYes
  5. 5API accessYes
  6. 6Speaker labelingYes
  7. 7Command controlYes
  8. 8Deploymenton device
8 lines stated Written from the maker's own pages: cmusphinx.github.io
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The CMU Sphinx homepage

Overview

CMU Sphinx is ranked #4 of 28 in speech recognition software on Specifiction. It runs on Android, Linux, macOS, Self-hosted, Windows. There is a free plan.

CMU Sphinx plans and pricing

All plans
CMU Sphinx toolkit Free BSD-like license · commercial distribution allowed cmusphinx.github.io · 5 Oct 2026

Compared on speech recognition software

Real-time recognition
Yescmusphinx.github.io
Offline recognition
Yescmusphinx.github.io
API access
Yescmusphinx.github.io
Speaker labeling
Yescmusphinx.github.io
Command control
Yescmusphinx.github.io
Deployment
on_devicecmusphinx.github.io

Facts

Purpose
CMU Sphinx is an open-source speech recognition toolkit for building speech applications.cmusphinx.github.io · 5 Oct 2026
Maintained components
The currently maintained components are PocketSphinx, a lightweight C recognizer library, and SphinxTrain, acoustic model training tools.cmusphinx.github.io · 5 Oct 2026
Low-resource design
The tools are designed for efficient speech recognition on low-resource platforms.cmusphinx.github.io · 5 Oct 2026
Languages
CMU Sphinx is language-independent, but recognition requires acoustic and language models; the site lists prebuilt models for languages including English, Chinese, French, Spanish, German, and Russian.cmusphinx.github.io · 5 Oct 2026
Model training
SphinxTrain provides acoustic model training tools, and the toolkit describes collecting data, cleaning it, training a model, and testing it to add a language.cmusphinx.github.io · 5 Oct 2026
Recognition features
The toolkit supports keyword spotting, grammar searches, language-model searches, and word-level segmentation through its documented interfaces.pocketsphinx.readthedocs.io · 5 Oct 2026
Noise handling
CMU Sphinx uses mel-cepstrum MFCC features with noise tracking and spectral subtraction for noise reduction.cmusphinx.github.io · 5 Oct 2026
Commercial use
The site describes its license as BSD-like and says it allows commercial distribution.cmusphinx.github.io · 5 Oct 2026
Support
The site describes commercial support and directs users to GitHub project and issue trackers for help.cmusphinx.github.io · 5 Oct 2026
Developer audience
The developer tutorial is intended for developers applying speech technology in applications, rather than speech-recognition researchers.cmusphinx.github.io · 5 Oct 2026
Use cases
The tutorial lists voice control, language learning, transcription, closed captioning, speech translation, and voice search as possible applications.cmusphinx.github.io · 5 Oct 2026
Android support
The site documents a PocketSphinx Android library and demo, while cautioning that the tutorial has not been tested for quite some time and may no longer work with current Android tools.cmusphinx.github.io · 5 Oct 2026
Platform constraints
The FAQ says large-vocabulary speech recognition is too computationally demanding for phones and other small embedded devices, where limited vocabularies are commonly used.cmusphinx.github.io · 5 Oct 2026
Input audio requirement
The decoders do not convert encoded audio formats, so audio must be converted to PCM before processing.cmusphinx.github.io · 5 Oct 2026
Current release
The homepage announces PocketSphinx 5.1.0, released May 6, 2026, with Python 3.14 support and prebuilt Linux/arm64 wheels.cmusphinx.github.io · 5 Oct 2026

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Where it ranks on Specifiction

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