Package: pvporcupinedemo
Porcupine Wake Word Engine DemosMade in Vancouver, Canada byPicovoiceThis package contains demos and commandline utilities for processing real-time audio (i.e. microphone) and audio files
using Porcupine wake word engine.PorcupinePorcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled
applications. It isusing deep neural networks trained in real-world environments.compact and computationally-efficient making it perfect for IoT.scalable. It can detect multiple always-listening voice commands with no added CPU/memory footprint.self-service. Developers can train custom wake phrases usingPicovoice Console.CompatibilityPython 3.5+Runs on Linux (x86_64), Mac (x86_64 and arm64), Windows (x86_64), Raspberry Pi (all variants), NVIDIA Jetson (Nano), and BeagleBone.Installationsudo pip3 install pvporcupinedemoAccessKeyPorcupine requires a valid PicovoiceAccessKeyat initialization.AccessKeyacts as your credentials when using Porcupine SDKs.
You can get yourAccessKeyfor free. Make sure to keep yourAccessKeysecret.
Signup or Login toPicovoice Consoleto get yourAccessKey.UsageMicrophone DemoIt opens an audio stream from a microphone and detects utterances of a given wake word. The following opens the default
microphone and detects occurrences of "Picovoice".porcupine_demo_mic --access_key ${ACCESS_KEY} --keywords picovoicekeywordsis a shorthand for using default keyword files shipped with the package. The list of default keyword files
can be seen in the usage stringporcupine_demo_mic --helpTo detect multiple phrases concurrently provide them as separate argumentsporcupine_demo_mic --access_key ${ACCESS_KEY} --keywords picovoice porcupineTo detect non-default keywords (e.g. models created usingPicovoice Console)
usekeyword_pathsargumentporcupine_demo_mic --access_key ${ACCESS_KEY} --keyword_paths ${KEYWORD_PATH_ONE} ${KEYWORD_PATH_TWO}To detect non-English keywords provide the respective model path:porcupine_demo_mic --access_key ${ACCESS_KEY} --model_path ${NON_ENGLISH_MODEL_PATH} --keyword_paths ${NON_ENGLISH_KEYWORD_PATH}The model files for all supported languages are availablehereon Porcupine's GitHub repository.It is possible that the default audio input device recognized by the demo is not the one being used. There are a couple of
debugging facilities baked into the demo application to solve this. First, type the following into the console:porcupine_demo_mic --show_audio_devicesIt provides information about various audio input devices on the box. On a Linux box, this is the console outputindex: 0, device name: USB Audio Device
index: 1, device name: MacBook Air MicrophoneYou can use the device index to specify which microphone to use for the demo. For instance, if you want to use the USB Audio Device
in the above example, you can invoke the demo application as below:porcupine_demo_mic --access_key ${ACCESS_KEY} --keywords picovoice --audio_device_index 0If the problem persists we suggest storing the recorded audio into a file for inspection. This can be achieved byporcupine_demo_mic --access_key ${ACCESS_KEY} --keywords picovoice --audio_device_index 0 --output_path ~/test.wavIf after listening to stored file there is no apparent problem detected please open an issue.File DemoIt allows testing Porcupine on a corpus of audio files. The demo is mainly useful for quantitative performance
benchmarking. It accepts 16kHz audio files. Porcupine processes a single-channel audio stream if a stereo file is
provided it only processes the first (left) channel. The following processes a file looking for instances of the phrase
"Picovoice"porcupine_demo_file --access_key ${ACCESS_KEY} --wav_path ${AUDIO_PATH} --keywords picovoicekeywordsis a shorthand for using default keyword files shipped with the package. The list of default keyword files
can be seen in the usage stringporcupine_demo_file --helpTo detect multiple phrases concurrently provide them as separate argumentsporcupine_demo_file --access_key ${ACCESS_KEY} --wav_path ${AUDIO_PATH} --keywords grasshopper porcupineTo detect non-default keywords (e.g. models created usingPicovoice Console)
usekeyword_pathsargumentporcupine_demo_file --access_key ${ACCESS_KEY} \--wav_path ${AUDIO_PATH} \--keyword_paths ${KEYWORD_PATH_ONE} ${KEYWORD_PATH_TWO}To detect non-English keywords provide the respective model path:porcupine_demo_mic --access_key ${ACCESS_KEY} \--wav_path ${AUDIO_PATH} \--model_path ${NON_ENGLISH_MODEL_PATH} \--keyword_paths ${NON_ENGLISH_KEYWORD_PATH}The model files for all supported languages are availablehereon Porcupine's GitHub repository.The sensitivity of the engine can be tuned per keyword using thesensitivitiesinput argumentporcupine_demo_file --access_key ${ACCESS_KEY} \--wav_path ${AUDIO_PATH} \--keywords grasshopper porcupine --sensitivities 0.3 0.6Sensitivity is the parameter that enables trading miss rate for the false alarm rate. It is a floating point number within[0, 1]. A higher sensitivity reduces the miss rate at the cost of increased false alarm rate.