树莓派使用Snowboy做离线语音识别关键字。

Voice Engine ============ [](https://travis-ci.org/voice-engine/voice-engine) [](https://pypi.python.org/pypi/voice-engine) The library is used to create voice interface applications. It includes building blocks such as KWS (keyword spotting), DOA (Direction Of Arrival). There are also elements to measure RMS (dBFS or dB(A)). ### Requirements + pyaudio + numpy + snowboy ### Installation Install pyaudio, numpy and snowboy, use virtualenv a virtual python environment. ``` sudo apt install python-pyaudio python-numpy python-virtualenv sudo apt-get install swig python-dev libatlas-base-dev build-essential make git clone --depth 1 https://github.com/Kitt-AI/snowboy.git cd snowboy virtualenv --system-site-packages env source env/bin/activate python setup.py build python setup.py bdist_wheel pip install dist/snowboy*.whl cd .. git clone https://github.com/voice-engine/voice-engine.git cd voice-engine python setup.py bdist_wheel pip install dist/*.whl ``` ### Get started To record audio and search keyword "snowboy", see also [`kws_snowboy.py`](voice_engine/kws_snowboy.py) ```python import time from voice_engine.kws import KWS from voice_engine.source import Source src = Source() kws = KWS() src.link(kws) def on_detected(keyword): print('found {}'.format(keyword)) kws.on_detected = on_detected kws.start() src.start() while True: try: time.sleep(1) except KeyboardInterrupt: break kws.stop() src.stop() ``` ### Building blocks The library uses gstreamer-like [elements](voice_engine/element.py) which can be linked together as an audio pipeline. One element can connect to more than one other elements. The topology can be: ``` Source --> ChannelPicker --> KWS Source --> ChannelPicker --> KWS --> Alexa | /\ V / \ DOA Alexa Google Asissitant ```