Picovoice Platform — Python API

This document outlines how to integrate Picovoice platform within an application using its Python API.

Requirements

• Python3
• PIP

Compatibility

• Linux (x86_64)
• macOS (x86_64)
• Windows (x86_64)
• Raspberry Pi (all variants)
• BeagleBone.

Installation

pip3 install picovoice

Usage

Create a new instance of Picovoice runtime engine

from picovoice import Picovoice
 
keyword_path = ...
 
def wake_word_callback():
    pass
 
context_path = ...
 
def inference_callback(inference):
    # `inference` exposes three immutable fields:
    # (1) `is_understood`
    # (2) `intent`
    # (3) `slots`
    pass
 
handle = Picovoice(
        keyword_path=keyword_path,
        wake_word_callback=wake_word_callback,
        context_path=context_path,
        inference_callback=inference_callback)

handle is an instance of Picovoice runtime engine that detects utterances of wake phrase defined in the file located at keyword_path. Upon detection of wake word it starts inferring user's intent from the follow-on voice command within the context defined by the file located at context_path. keyword_path is the absolute path to Porcupine wake word engine keyword file (with .ppn suffix). context_path is the absolute path to Rhino Speech-to-Intent engine context file (with .rhn suffix). wake_word_callback is invoked upon the detection of wake phrase and inference_callback is invoked upon completion of follow-on voice command inference.

When instantiated, valid sample rate can be obtained via handle.sample_rate. Expected number of audio samples per frame is handle.frame_length. The engine accepts 16-bit linearly-encoded PCM and operates on single-channel audio.

def get_next_audio_frame():
    pass
 
while True:
    handle.process(get_next_audio_frame())

When done resources have to be released explicitly

handle.delete()