Uberi/speech_recognition

SpeechRecognition ================= .. image:: https://img.shields.io/pypi/v/SpeechRecognition.svg :target: https://pypi.python.org/pypi/SpeechRecognition/ :alt: Latest Version .. image:: https://img.shields.io/pypi/status/SpeechRecognition.svg :target: https://pypi.python.org/pypi/SpeechRecognition/ :alt: Development Status .. image:: https://img.shields.io/pypi/pyversions/SpeechRecognition.svg :target: https://pypi.python.org/pypi/SpeechRecognition/ :alt: Supported Python Versions .. image:: https://img.shields.io/pypi/l/SpeechRecognition.svg :target: https://pypi.python.org/pypi/SpeechRecognition/ :alt: License .. image:: https://api.travis-ci.org/Uberi/speech_recognition.svg?branch=master :target: https://travis-ci.org/Uberi/speech_recognition :alt: Continuous Integration Test Results .. image:: https://deepwiki.com/badge.svg :target: https://deepwiki.com/Uberi/speech_recognition :alt: Ask DeepWiki .. image:: https://www.gstatic.com/_/boq-sdlc-agents-ui/_/r/Mvosg4klCA4.svg :target: https://codewiki.google/github.com/Uberi/speech_recognition :alt: Ask Code Wiki :height: 20px .. image:: https://img.shields.io/badge/docs-Mintlify-0ea5e9?logo=mintlify&logoColor=white :target: https://mintlify.com/Uberi/speech_recognition :alt: Mintlify Docs (Auto generated) .. image:: https://img.shields.io/badge/Docs-Context7-6C47FF :target: https://context7.com/uberi/speech_recognition :alt: Context7 Library for performing speech recognition, with support for several engines and APIs, online and offline. Recall.ai - Meeting Transcription API ------------------------------------- If you’re working with speech detection or transcription for meetings, consider checking out Recall.ai __, an API that works with Zoom, Google Meet, Microsoft Teams, and more. Recall.ai diarizes by pulling the speaker data and separate audio streams from the meeting platforms, which means 100% accurate speaker diarization with actual speaker names and speaker emails. Getting Started --------------- Speech recognition engine/API support:

• CMU Sphinx __ (works offline)
• Google Speech Recognition
• Google Cloud Speech API __
• Wit.ai __
• Microsoft Azure Speech __
• Houndify API __
• IBM Speech to Text __
• Snowboy Hotword Detection __ (works offline)
• Tensorflow __
• Vosk API __ (works offline)
• OpenAI whisper __ (works offline)
• OpenAI Transcription API __
• OpenAI compatible self-hosted endpoints (e.g. vLLM, Ollama)
• Groq Whisper API __
• Cohere Transcribe API __

Quickstart: `pip install SpeechRecognition`. See the "Installing" section for more details. To quickly try it out, run `python -m speech_recognition` after installing. Project links:

• PyPI __
• Source code __
• Issue tracker __

Library Reference ----------------- The library reference __ documents every publicly accessible object in the library. This document is also included under `reference/library-reference.rst`. See Notes on using PocketSphinx __ for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under `reference/pocketsphinx.rst`. Examples -------- See the `examples/ directory `__ in the repository root for usage examples:

• Recognize speech input from the microphone __
• Transcribe an audio file __
• Save audio data to an audio file __
• Show extended recognition results __
• Calibrate the recognizer energy threshold for ambient noise levels __ (see `recognizer_instance.energy_threshold` for details)
• Listening to a microphone in the background __
• Various other useful recognizer features __

Installing ---------- First, make sure you have all the requirements listed in the "Requirements" section. The easiest way to install this is using `pip install SpeechRecognition`. Otherwise, download the source distribution from PyPI __, and extract the archive. In the folder, run `python -m pip install .`. Requirements ------------ To use all of the functionality of the library, you should have:

• Python 3.10+ (required)
• PyAudio 0.2.11+ (required only if you need to use microphone input, `Microphone`)
• PocketSphinx (required only if you need to use the Sphinx recognizer, `recognizer_instance.recognize_sphinx`)
• Google API Client Library for Python (required only if you need to use the Google Cloud Speech API, `recognizer_instance.recognize_google_cloud`)
• FLAC encoder (required only if the system is not x86-based Windows/Linux/OS X)
• Vosk (required only if you need to use Vosk API speech recognition `recognizer_instance.recognize_vosk`)
• Whisper (required only if you need to use Whisper `recognizer_instance.recognize_whisper`)
• Faster Whisper (required only if you need to use Faster Whisper `recognizer_instance.recognize_faster_whisper`)
• openai (required only if you need to use OpenAI Transcription API speech recognition `recognizer_instance.recognize_openai`)
• includes OpenAI compatible self-hosted endpoints (e.g. vLLM, Ollama)
• groq (required only if you need to use Groq Whisper API speech recognition `recognizer_instance.recognize_groq`)
• cohere (required only if you need to use Cohere Transcribe API speech recognition `recognizer_instance.recognize_cohere_api; install with pip install SpeechRecognition[cohere-api]. Set CO_API_KEY` as documented by the Cohere SDK.)

The following requirements are optional, but can improve or extend functionality in some situations:

• If using CMU Sphinx, you may want to install additional language packs __ to support languages like International French or Mandarin Chinese.

The following sections go over the details of each requirement. Python ~~~~~~ The first software requirement is Python 3.10+ __. This is required to use the library. PyAudio (for microphone users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PyAudio __ is required if and only if you want to use microphone input (`Microphone`). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. If not installed, everything in the library will still work, except attempting to instantiate a `Microphone object will raise an AttributeError`. The installation instructions on the PyAudio website are quite good - for convenience, they are summarized below:

• On Windows, install with PyAudio using Pip __: execute `pip install SpeechRecognition[audio]` in a terminal.
• On Debian-derived Linux distributions (like Ubuntu and Mint), install PyAudio using APT __: execute `sudo apt-get install python-pyaudio python3-pyaudio` in a terminal.
• If the version in the repositories is too old, install the latest release using Pip: execute `sudo apt-get install portaudio19-dev python-all-dev python3-all-dev && sudo pip install SpeechRecognition[audio] (replace pip with pip3` if using Python 3).
• On OS X, install PortAudio using Homebrew __: `brew install portaudio. Then, install with PyAudio using Pip __: pip install SpeechRecognition[audio]`.
• On other POSIX-based systems, install the `portaudio19-dev and python-all-dev (or python3-all-dev if using Python 3) packages (or their closest equivalents) using a package manager of your choice, and then install with PyAudio using Pip __: pip install SpeechRecognition[audio] (replace pip with pip3` if using Python 3).

PocketSphinx (for Sphinx users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PocketSphinx __ is required if and only if you want to use the Sphinx recognizer (`recognizer_instance.recognize_sphinx`). On Linux and other POSIX systems (such as OS X), run `pip install SpeechRecognition[pocketsphinx]. Follow the instructions under "Building PocketSphinx-Python from source" in Notes on using PocketSphinx `__ for installation instructions. Note that the versions available in most package repositories are outdated and will not work with the bundled language data. Using the bundled wheel packages or building from source is recommended. See Notes on using PocketSphinx __ for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under `reference/pocketsphinx.rst`. Vosk (for Vosk users) ~~~~~~~~~~~~~~~~~~~~~ Vosk API is required if and only if you want to use Vosk recognizer (`recognizer_instance.recognize_vosk`). You can install it with `python3 -m pip install SpeechRecognition[vosk]`. You also have to install Vosk Models: Here __ are models available for download. You have to place them in the `model` directory of your project, like "your-project-folder/model". You can also run `sprc download vosk` to download the default model. Google Cloud Speech Library for Python (for Google Cloud Speech-to-Text API users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The library google-cloud-speech __ is required if and only if you want to use Google Cloud Speech-to-Text API (`recognizer_instance.recognize_google_cloud`). You can install it with `python3 -m pip install SpeechRecognition[google-cloud]`. (ref: official installation instructions __) Prerequisite: Create local authentication credentials for your Google account

• Digest: Before you begin (Transcribe speech to text by using client libraries) __
• Set up Speech-to-Text __
• User credentials (Set up ADC for a local development environment) __

Currently only V1 __ is supported. (V2 __ is not supported) FLAC (for some systems) ~~~~~~~~~~~~~~~~~~~~~~~ A FLAC encoder __ is required to encode the audio data to send to the API. If using Windows (x86 or x86-64), OS X (Intel Macs only, OS X 10.6 or higher), or Linux (x86 or x86-64), this is already bundled with this library - you do not need to install anything. Otherwise, ensure that you have the `flac command line tool, which is often available through the system package manager. For example, this would usually be sudo apt-get install flac on Debian-derivatives, or brew install flac` on OS X with Homebrew. Whisper (for Whisper users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Whisper is required if and only if you want to use whisper (`recognizer_instance.recognize_whisper`). You can install it with `python3 -m pip install SpeechRecognition[whisper-local]`. Faster Whisper (for Faster Whisper users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The library faster-whisper __ is required if and only if you want to use Faster Whisper (`recognizer_instance.recognize_faster_whisper`). You can install it with `python3 -m pip install SpeechRecognition[faster-whisper]`. OpenAI Transcription API (for OpenAI Transcription API users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The library openai __ is required if and only if you want to use OpenAI Transcription API (`recognizer_instance.recognize_openai`). You can install it with `python3 -m pip install SpeechRecognition[openai]`. Please set the environment variable `OPENAI_API_KEY before calling recognizer_instance.recognize_openai`. OpenAI-compatible self-hosted Whisper endpoints (for users of vLLM, Ollama, etc.) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `recognizer_instance.recognize_openai` also supports OpenAI-compatible endpoints. Set `OPENAI_BASE_URL to point to your custom endpoint with dummy OPENAI_API_KEY`. Groq Whisper API (for Groq Whisper API users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The library groq __ is required if and only if you want to use Groq Whisper API (`recognizer_instance.recognize_groq`). You can install it with `python3 -m pip install SpeechRecognition[groq]`. Please set the environment variable `GROQ_API_KEY before calling recognizer_instance.recognize_groq`. Troubleshooting --------------- The recognizer tries to recognize speech even when I'm not speaking, or after I'm done speaking. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Try increasing the `recognizer_instance.energy_threshold` property. This is basically how sensitive the recognizer is to when recognition should start. Higher values mean that it will be less sensitive, which is useful if you are in a loud room. This value depends entirely on your microphone or audio data. There is no one-size-fits-all value, but good values typically range from 50 to 4000. Also, check on your microphone volume settings. If it is too sensitive, the microphone may be picking up a lot of ambient noise. If it is too insensitive, the microphone may be rejecting speech as just noise. The recognizer can't recognize speech right after it starts listening for the first time. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `recognizer_instance.energy_threshold` property is probably set to a value that is too high to start off with, and then being adjusted lower automatically by dynamic energy threshold adjustment. Before it is at a good level, the energy threshold is so high that speech is just considered ambient noise. The solution is to decrease this threshold, or call `recognizer_instance.adjust_for_ambient_noise` beforehand, which will set the threshold to a good value automatically. The recognizer doesn't understand my particular language/dialect. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Try setting the recognition language to your language/dialect. To do this, see the documentation for `recognizer_instance.recognize_sphinx, recognizer_instance.recognize_google, recognizer_instance.recognize_wit, recognizer_instance.recognize_api, recognizer_instance.recognize_houndify, and recognizer_instance.recognize_ibm`. For example, if your language/dialect is British English, it is better to use `"en-GB" as the language rather than "en-US"`. The recognizer hangs on `recognizer_instance.listen; specifically, when it's calling Microphone.MicrophoneStream.read`. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This usually happens when you're using a Raspberry Pi board, which doesn't have audio input capabilities by itself. This causes the default microphone used by PyAudio to simply block when we try to read it. If you happen to be using a Raspberry Pi, you'll need a USB sound card (or USB microphone). Once you do this, change all instances of `Microphone() to Microphone(device_index=MICROPHONE_INDEX), where MICROPHONE_INDEX` is the hardware-specific index of the microphone. To figure out what the value of `MICROPHONE_INDEX` should be, run the following code: .. code:: python import speech_recognition as sr for index, name in enumerate(sr.Microphone.list_microphone_names()): print("Microphone with name \"{1}\" found for Microphone(device_index={0})".format(index, name)) This will print out something like the following: :: Microphone with name "HDA Intel HDMI: 0 (hw:0,3)" found for Microphone(device_index=0) Microphone with name "HDA Intel HDMI: 1 (hw:0,7)" found for Microphone(device_index=1) Microphone with name "HDA Intel HDMI: 2 (hw:0,8)" found for Microphone(device_index=2) Microphone with name "Blue Snowball: USB Audio (hw:1,0)" found for Microphone(device_index=3) Microphone with name "hdmi" found for Microphone(device_index=4) Microphone with name "pulse" found for Microphone(device_index=5) Microphone with name "default" found for Microphone(device_index=6) Now, to use the Snowball microphone, you would change `Microphone() to Microphone(device_index=3)`. Calling `Microphone() gives the error IOError: No Default Input Device Available`. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ As the error says, the program doesn't know which microphone to use. To proceed, either use `Microphone(device_index=MICROPHONE_INDEX, ...) instead of Microphone(...), or set a default microphone in your OS. You can obtain possible values of MICROPHONE_INDEX` using the code in the troubleshooting entry right above this one. The program doesn't run when compiled with PyInstaller __. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ As of PyInstaller version 3.0, SpeechRecognition is supported out of the box. If you're getting weird issues when compiling your program using PyInstaller, simply update PyInstaller. You can easily do this by running `pip install --upgrade pyinstaller`. On Ubuntu/Debian, I get annoying output in the terminal saying things like "bt_audio_service_open: [...] Connection refused" and various others. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The "bt_audio_service_open" error means that you have a Bluetooth audio device, but as a physical device is not currently connected, we can't actually use it - if you're not using a Bluetooth microphone, then this can be safely ignored. If you are, and audio isn't working, then double check to make sure your microphone is actually connected. There does not seem to be a simple way to disable these messages. For errors of the form "ALSA lib [...] Unknown PCM", see this StackOverflow answer __. Basically, to get rid of an error of the form "Unknown PCM cards.pcm.rear", simply comment out `pcm.rear cards.pcm.rear in /usr/share/alsa/alsa.conf, ~/.asoundrc, and /etc/asound.conf`. For "jack server is not running or cannot be started" or "connect(2) call to /dev/shm/jack-1000/default/jack_0 failed (err=No such file or directory)" or "attempt to connect to server failed", these are caused by ALSA trying to connect to JACK, and can be safely ignored. I'm not aware of any simple way to turn those messages off at this time, besides entirely disabling printing while starting the microphone __. On OS X, I get a `ChildProcessError` saying that it couldn't find the system FLAC converter, even though it's installed. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Installing FLAC for OS X __ directly from the source code will not work, since it doesn't correctly add the executables to the search path. Installing FLAC using Homebrew __ ensures that the search path is correctly updated. First, ensure you have Homebrew, then run `brew install flac` to install the necessary files. Contributing ------------ See CONTRIBUTING.rst __ for information on setting up a development environment, running tests, and contribution guidelines. Authors ------- :: Uberi (Anthony Zhang) bobsayshilol arvindch (Arvind Chembarpu) kevinismith <[email protected]> (Kevin Smith) haas85 DelightRun maverickagm kamushadenes (Kamus Hadenes) sbraden (Sarah Braden) tb0hdan (Bohdan Turkynewych) Thynix (Steve Dougherty) beeedy (Broderick Carlin) Please report bugs and suggestions at the issue tracker __! How to cite this library (APA style): Zhang, A. (2017). Speech Recognition (Version 3.11) [Software]. Available from https://github.com/Uberi/speech_recognition#readme. How to cite this library (Chicago style): Zhang, Anthony. 2017. Speech Recognition (version 3.11). Also check out the Python Baidu Yuyin API __, which is based on an older version of this project, and adds support for Baidu Yuyin __. Note that Baidu Yuyi