picovoice 2.0.1

Picovoice is an end-to-end platform for building voice products on your terms.

Picovoice

Made in Vancouver, Canada by Picovoice

Picovoice is an end-to-end platform for building voice products on your terms. It enables creating voice experiences similar to Alexa and Google. But it entirely runs 100% on-device. Picovoice is

• Private: Everything is processed offline. Intrinsically HIPAA and GDPR-compliant.
• Reliable: Runs without needing constant connectivity.
• Zero Latency: Edge-first architecture eliminates unpredictable network delay.
• Accurate: Resilient to noise and reverberation. It outperforms cloud-based alternatives by wide margins *.
• Cross-Platform: Design once, deploy anywhere. Build using familiar languages and frameworks.

Compatibility

• Python 3
• Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (all variants), NVIDIA Jetson (Nano), and BeagleBone.

Installation

pip3 install picovoice

AccessKey

Picovoice requires a valid AccessKey at initialization. AccessKeys act as your credentials when using Picovoice SDKs. You can create your AccessKey for free. Make sure to keep your AccessKey secret.

To obtain your AccessKey:

1. Login or Signup for a free account on the Picovoice Console.
2. Once logged in, go to the AccessKey tab to create one or use an existing AccessKey.

Usage

Create a new instance of Picovoice runtime engine

from picovoice import Picovoice

access_key = "${ACCESS_KEY}" # AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)

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(
        access_key=access_key,
        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()

Non-English Models

In order to detect wake words and run inference in other languages you need to use the corresponding model file. The model files for all supported languages are available here and here.

Demos

picovoicedemo provides command-line utilities for processing real-time audio (i.e. microphone) and files using Picovoice platform.