Picovoice Platform — Java API
This document outlines how to integrate Picovoice platform within an application using its Java API.
Requirements
- Java 11+
Compatibility
- Linux (x86_64)
- macOS (x86_64)
- Windows (x86_64)
Installation
You can add the Picovoice Java SDK by downloading and referencing the latest Picovoice JAR.
Build
To build from source, we recommend using the IntelliJ IDE. Open the .iml file with IntelliJ and click "Build > Build Project" to build or "Build > Build Artifacts" to package as a JAR file.
Usage
The easiest way to create an instance of the engine is with the Picovoice Builder:
import ai.picovoice.picovoice.*;String keywordPath = "/absolute/path/to/keyword.ppn"PicovoiceWakeWordCallback wakeWordCallback = () -> {..};String contextPath = "/absolute/path/to/context.rhn"PicovoiceInferenceCallback inferenceCallback = inference -> {// `inference` exposes three getters:// (1) `getIsUnderstood()`// (2) `getIntent()`// (3) `getSlots()`// ..};try{Picovoice handle = new Picovoice.Builder().setKeywordPath(keywordPath).setWakeWordCallback(wakeWordCallback).setContextPath(contextPath).setInferenceCallback(inferenceCallback).build();} catch (PicovoiceException e) { }
handle
is an instance of Picovoice runtime engine that detects utterances of wake phrase defined in the file located at
keywordPath
. 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 contextPath
. keywordPath
is the absolute path to
Porcupine wake word engine keyword file (with .ppn
suffix).
contextPath
is the absolute path to Rhino Speech-to-Intent engine context file
(with .rhn
suffix). wakeWordCallback
is invoked upon the detection of wake phrase and inferenceCallback
is
invoked upon completion of follow-on voice command inference.
When instantiated, valid sample rate can be obtained via handle.getSampleRate()
. Expected number of audio samples per
frame is handle.getFrameLength()
. The engine accepts 16-bit linearly-encoded PCM and operates on single-channel audio.
short[] getNextAudioFrame(){// .. get audioFramereturn audioFrame;}while(true){handle.process(getNextAudioFrame());}
Once you're done with Picovoice, ensure you release its resources explicitly:
handle.delete();
Custom Wake Word & Context
You can create custom Porcupine wake word and Rhino context models using Picovoice Console