Library for performing speech recognition with the Google Speech Recognition API.
Links:
Quickstart: pip install SpeechRecognition
Recognize speech input from the microphone:
# NOTE: this requires PyAudio because it uses the Microphone class
import speech_recognition as sr
r = sr.Recognizer()
with sr.Microphone() as source: # use the default microphone as the audio source
audio = r.listen(source) # listen for the first phrase and extract it into audio data
try:
print("You said " + r.recognize(audio)) # recognize speech using Google Speech Recognition
except LookupError: # speech is unintelligible
print("Could not understand audio")Transcribe a WAV audio file:
import speech_recognition as sr
r = sr.Recognizer()
with sr.WavFile("test.wav") as source: # use "test.wav" as the audio source
audio = r.record(source) # extract audio data from the file
try:
print("Transcription: " + r.recognize(audio)) # recognize speech using Google Speech Recognition
except LookupError: # speech is unintelligible
print("Could not understand audio")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.
This is available if PyAudio is available, and is undefined otherwise.
Creates a new Microphone instance, which represents a physical
microphone on the computer. Subclass of AudioSource.
If device_index is unspecified or None, the default microphone
is used as the audio source. Otherwise, device_index should be the
index of the device to use for audio input.
A device index is an integer between 0 and
pyaudio.get_device_count() - 1 (assume we have used
import pyaudio beforehand) inclusive. It represents an audio device
such as a microphone or speaker. See the PyAudio
documentation for
more details.
This class is to be used with with statements:
with Microphone() as source: # open the microphone and start recording
pass # do things here - `source` is the Microphone instance created above
# the microphone is automatically released at this point
Creates a new WavFile instance, which represents a WAV audio file.
Subclass of AudioSource.
If filename_or_fileobject is a string, then it is interpreted as a
path to a WAV audio file on the filesystem. Otherwise,
filename_or_fileobject should be a file-like object such as
io.BytesIO or similar. In either case, the specified file is used as
the audio source.
This class is to be used with with statements:
with WavFile("test.wav") as source: # open the WAV file for reading
pass # do things here - `source` is the WavFile instance created above
Creates a new Recognizer instance, which represents a collection of
speech recognition functionality.
The language is determined by language, a standard language code,
and defaults to US English.
Represents the energy level threshold for sounds. Values below this threshold are considered silence. Can be changed.
This threshold is associated with the perceived loudness of the sound, but it is a nonlinear relationship. Typical values for a silent room are 0 to 1, and typical values for speaking are between 150 and 3500.
Represents the minimum length of silence (in seconds) that will register as the end of a phrase. Can be changed.
Smaller values result in the recognition completing more quickly, but might result in slower speakers being cut off.
Records up to duration seconds of audio from source (an
AudioSource instance) into an AudioData instance, which it
returns.
If duration is not specified, then it will record until there is no
more audio input.
Records a single phrase from source (an AudioSource instance)
into an AudioData instance, which it returns.
This is done by waiting until the audio has an energy above
recognizer_instance.energy_threshold (the user has started
speaking), and then recording until it encounters
recognizer_instance.pause_threshold seconds of silence or there is
no more audio input. The ending silence is not included.
Performs speech recognition, using the Google Speech Recognition API, on
audio_data (an AudioData instance).
Returns the recognized text if successful, and raises a LookupError
exception if the speech is unintelligible.
Base class representing audio sources. Do not instantiate.
Instances of subclasses of this class, such as Microphone and
WavFile, can be passed to things like recognizer_instance.record
and recognizer_instance.listen.
Storage class for audio data.
Contains the fields rate and data, which represent the framerate
and raw audio samples of the audio data, respectively.
Google Speech API v2 now requires a key.
Follow the steps: http://www.chromium.org/developers/how-tos/api-keys
The first requirement is Python 3.3 or better. This is required to use the library.
Additionally, it must be 32-bit Python if you are using the included PyAudio binaries. It is also technically possible though inconvenient to compile PyAudio for 64-bit Python.
If you want to use the Microphone class (necessary for recording
from microphone input),
PyAudio is
also necessary. If not installed, the library will still work, but
Microphone will be undefined.
The official PyAudio builds seem to be broken on Windows. As a result,
in the installers folder you will find unofficial builds for
Windows that
actually work. Run installers/PyAudio-0.2.7.win32-py3.3.exe for
Python 3.3 and PyAudio-0.2.7.win32-py3.4.exe for Python 3.4.
A FLAC encoder is required to encode the audio data to send to the API.
If using Windows or Linux, the encoder is already bundled with this
library. Otherwise, ensure that you have the flac command line tool,
which is often available through one's system package manager.
Copyright 2014 Anthony Zhang [email protected] (Uberi).
The source code is available online at GitHub.
This program is made available under the 3-clause BSD license. See
LICENSE.txt for more information.