Speech recognition module for Python, supporting several engines and APIs, online and offline.
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Library for performing speech recognition, with support for several engines and APIs, online and offline.
Speech recognition engine/API support:
CMU Sphinx__ (works offline)
Google Cloud Speech API__
Wit.ai__
Microsoft Azure Speech__
Microsoft Bing Voice Recognition (Deprecated)__
Houndify API__
IBM Speech to Text__
Snowboy Hotword Detection__ (works offline)
Quickstart:
pip install SpeechRecognition. See the "Installing" section for more details.
To quickly try it out, run
python -m speech_recognitionafter installing.
Project links:
PyPI__
Source code__
Issue tracker__
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.
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_thresholdfor details)
Listening to a microphone in the background__
Various other useful recognizer features__
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 setup.py install.
To use all of the functionality of the library, you should have:
Microphone)
recognizer_instance.recognize_sphinx)
recognizer_instance.recognize_google_cloud)
The following requirements are optional, but can improve or extend functionality in some situations:
recognizer_instance.recognize_bing) will run slower if you do not have Monotonic for Python 2 installed.
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 2.6, 2.7, or Python 3.3+__. 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
Microphoneobject will raise an
AttributeError.
The installation instructions on the PyAudio website are quite good - for convenience, they are summarized below:
Pip__: execute
pip install pyaudioin a terminal.
APT__: execute
sudo apt-get install python-pyaudio python3-pyaudioin a terminal.
sudo apt-get install portaudio19-dev python-all-dev python3-all-dev && sudo pip install pyaudio(replace
pipwith
pip3if using Python 3).
Homebrew:
brew install portaudio. Then, install PyAudio using
Pip:
pip install pyaudio.
portaudio19-devand
python-all-dev(or
python3-all-devif using Python 3) packages (or their closest equivalents) using a package manager of your choice, and then install PyAudio using
Pip__:
pip install pyaudio(replace
pipwith
pip3if using Python 3).
PyAudio
wheel packages__ for common 64-bit Python versions on Windows and Linux are included for convenience, under the
third-party/
directory__ in the repository root. To install, simply run
pip install wheelfollowed by
pip install ./third-party/WHEEL_FILENAME(replace
pipwith
pip3if using Python 3) in the repository
root directory__.
PocketSphinx-Python (for Sphinx users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
PocketSphinx-Python__ is required if and only if you want to use the Sphinx recognizer (
recognizer_instance.recognize_sphinx).
PocketSphinx-Python
wheel packages__ for 64-bit Python 2.7, 3.4, and 3.5 on Windows are included for convenience, under the
third-party/
directory_. To install, simply run
pip install wheelfollowed by ``pip install ./third-party/WHEELFILENAME
(replacepip
withpip3`` if using Python 3) in the SpeechRecognition folder.
On Linux and other POSIX systems (such as OS X), 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.
Google Cloud Speech Library for Python (for Google Cloud Speech API users) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Google Cloud Speech library for Python__ is required if and only if you want to use the Google Cloud Speech API (
recognizer_instance.recognize_google_cloud).
If not installed, everything in the library will still work, except calling
recognizer_instance.recognize_google_cloudwill raise an
RequestError.
According to the
official installation instructions, the recommended way to install this is using
Pip: execute
pip install google-cloud-speech(replace
pipwith
pip3if using Python 3).
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
flaccommand line tool, which is often available through the system package manager. For example, this would usually be
sudo apt-get install flacon Debian-derivatives, or
brew install flacon OS X with Homebrew.
Monotonic for Python 2 (for faster operations in some functions on Python 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
On Python 2, and only on Python 2, if you do not install the
Monotonic for Python 2__ library, some functions will run slower than they otherwise could (though everything will still work correctly).
On Python 3, that library's functionality is built into the Python standard library, which makes it unnecessary.
This is because monotonic time is necessary to handle cache expiry properly in the face of system time changes and other time-related issues. If monotonic time functionality is not available, then things like access token requests will not be cached.
To install, use
Pip__: execute
pip install monotonicin a terminal.
The recognizer tries to recognize speech even when I'm not speaking, or after I'm done speaking. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Try increasing the
recognizer_instance.energy_thresholdproperty. 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_thresholdproperty 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_noisebeforehand, 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_bing,
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_INDEXis the hardware-specific index of the microphone.
To figure out what the value of
MICROPHONE_INDEXshould 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_INDEXusing the code in the troubleshooting entry right above this one.
The code examples raise
UnicodeEncodeError: 'ascii' codec can't encode characterwhen run. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When you're using Python 2, and your language uses non-ASCII characters, and the terminal or file-like object you're printing to only supports ASCII, an error is raised when trying to write non-ASCII characters.
This is because in Python 2,
recognizer_instance.recognize_sphinx,
recognizer_instance.recognize_google,
recognizer_instance.recognize_wit,
recognizer_instance.recognize_bing,
recognizer_instance.recognize_api,
recognizer_instance.recognize_houndify, and
recognizer_instance.recognize_ibmreturn unicode strings (
u"something") rather than byte strings (
"something"). In Python 3, all strings are unicode strings.
To make printing of unicode strings work in Python 2 as well, replace all print statements in your code of the following form:
.. code:: pythonprint SOME_UNICODE_STRING
With the following:
.. code:: pythonprint SOME_UNICODE_STRING.encode("utf8")
This change, however, will prevent the code from working in Python 3.
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 "btaudioservice_open: [...] Connection refused" and various others. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The "btaudioservice_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.rearin
/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/jack0 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 <https://github.com/Uberi/speechrecognition/issues/182#issuecomment-266256337>`__.
On OS X, I get a
ChildProcessErrorsaying 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 flacto install the necessary files.
To hack on this library, first make sure you have all the requirements listed in the "Requirements" section.
speech_recognition/__init__.py.
examples/
directory, and the demo script lives in ``speech_recognition/main__.py``.
speech_recognition/
directory__.
reference/
directory__.
third-party/
directory__.
To install/reinstall the library locally, run
python setup.py installin the project
root directory__.
Before a release, the version number is bumped in
README.rstand
speech_recognition/__init__.py. Version tags are then created using
git config gpg.program gpg2 && git config user.signingkey DB45F6C431DE7C2DCD99FF7904882258A4063489 && git tag -s VERSION_GOES_HERE -m "Version VERSION_GOES_HERE".
Releases are done by running
make-release.sh VERSION_GOES_HEREto build the Python source packages, sign them, and upload them to PyPI.
Testing ~~~~~~~
To run all the tests:
.. code:: bash
python -m unittest discover --verbose
Testing is also done automatically by TravisCI, upon every push. To set up the environment for offline/local Travis-like testing on a Debian-like system:
.. code:: bash
sudo docker run --volume "$(pwd):/speech_recognition" --interactive --tty quay.io/travisci/travis-python:latest /bin/bash su - travis && cd /speech_recognition sudo apt-get update && sudo apt-get install swig libpulse-dev pip install --user pocketsphinx monotonic && pip install --user flake8 rstcheck && pip install --user -e . python -m unittest discover --verbose # run unit tests python -m flake8 --ignore=E501,E701 speech_recognition tests examples setup.py # ignore errors for long lines and multi-statement lines python -m rstcheck README.rst reference/*.rst # ensure RST is well-formed
FLAC Executables ~~~~~~~~~~~~~~~~
The included
flac-win32executable is the
official FLAC 1.3.2 32-bit Windows binary__.
The included
flac-linux-x86and
flac-linux-x86_64executables are built from the
FLAC 1.3.2 source code__ with
Manylinux__ to ensure that it's compatible with a wide variety of distributions.
The built FLAC executables should be bit-for-bit reproducible. To rebuild them, run the following inside the project directory on a Debian-like system:
.. code:: bash
# download and extract the FLAC source code cd third-party sudo apt-get install --yes docker.iobuild FLAC inside the Manylinux i686 Docker image
tar xf flac-1.3.2.tar.xz sudo docker run --tty --interactive --rm --volume "$(pwd):/root" quay.io/pypa/manylinux1_i686:latest bash cd /root/flac-1.3.2 ./configure LDFLAGS=-static # compiler flags to make a static build make exit cp flac-1.3.2/src/flac/flac ../speech_recognition/flac-linux-x86 && sudo rm -rf flac-1.3.2/
build FLAC inside the Manylinux x86_64 Docker image
tar xf flac-1.3.2.tar.xz sudo docker run --tty --interactive --rm --volume "$(pwd):/root" quay.io/pypa/manylinux1_x86_64:latest bash cd /root/flac-1.3.2 ./configure LDFLAGS=-static # compiler flags to make a static build make exit cp flac-1.3.2/src/flac/flac ../speech_recognition/flac-linux-x86_64 && sudo rm -r flac-1.3.2/
The included
flac-macexecutable is extracted from
xACT 2.39__, which is a frontend for FLAC 1.3.2 that conveniently includes binaries for all of its encoders. Specifically, it is a copy of
xACT 2.39/xACT.app/Contents/Resources/flacin
xACT2.39.zip.
::
Uberi (Anthony Zhang) bobsayshilol arvindch (Arvind Chembarpu) kevinismith (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 3.8) [Software]. Available from https://github.com/Uberi/speech_recognition#readme.
How to cite this library (Chicago style):
Zhang, Anthony. 2017. *Speech Recognition* (version 3.8).
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 Yuyin is only available inside China.
Copyright 2014-2017
Anthony Zhang (Uberi). The source code for this library is available online at
GitHub.
SpeechRecognition is made available under the 3-clause BSD license. See
LICENSE.txtin the project's
root directory__ for more information.
For convenience, all the official distributions of SpeechRecognition already include a copy of the necessary copyright notices and licenses. In your project, you can simply say that licensing information for SpeechRecognition can be found within the SpeechRecognition README, and make sure SpeechRecognition is visible to users if they wish to see it.
SpeechRecognition distributes source code, binaries, and language files from
CMU Sphinx_. These files are BSD-licensed and redistributable as long as copyright notices are correctly retained. See ``speechrecognition/pocketsphinx-data//LICENSE.txt
andthird-party/LICENSE-Sphinx.txt`` for license details for individual parts.
SpeechRecognition distributes source code and binaries from
PyAudio__. These files are MIT-licensed and redistributable as long as copyright notices are correctly retained. See
third-party/LICENSE-PyAudio.txtfor license details.
SpeechRecognition distributes binaries from
FLAC__ -
speech_recognition/flac-win32.exe,
speech_recognition/flac-linux-x86, and
speech_recognition/flac-mac. These files are GPLv2-licensed and redistributable, as long as the terms of the GPL are satisfied. The FLAC binaries are an
aggregate__ of
separate programs__, so these GPL restrictions do not apply to the library or your programs that use the library, only to FLAC itself. See
LICENSE-FLAC.txtfor license details.