Picovoice Platform
Java Quick Start

Platforms

• Linux (x86_64)
• macOS (x86_64, arm64)
• Windows (x86_64)
• Raspberry Pi (3, 4, 5)

Requirements

• Picovoice Account and AccessKey
• Java 11+

Picovoice Account & AccessKey

Signup or Login to Picovoice Console to get your AccessKey. Make sure to keep your AccessKey secret.

Quick Start

Setup

1. Install JDK 11+.

2. Install the Java binding from the Maven Central Repository at:

ai.picovoice:picovoice-java:${version}

Usage

Create an instance of Picovoice that uses a Porcupine keyword file, and a Rhino context file:

import ai.picovoice.picovoice.*;

PicovoiceWakeWordCallback wakeWordCallback = () -> {
  // ...
};

PicovoiceInferenceCallback inferenceCallback = inference -> {
    // ...
};

Picovoice picovoice = new Picovoice.Builder()
                      .setAccessKey("${ACCESS_KEY}")
                      .setKeywordPath("${KEYWORD_FILE_PATH}")
                      .setWakeWordCallback(wakeWordCallback)
                      .setContextPath("${CONTEXT_FILE_PATH}")
                      .setInferenceCallback(inferenceCallback)
                      .build();

Pass in frames of audio to the .process function:

short[] getNextAudioFrame() {
    // ...
    return audioFrame;
}

while(true) {
    picovoice.process(getNextAudioFrame());
}

Release resources explicitly when done with Picovoice:

picovoice.delete();

Custom Wake Words & Contexts

Create custom contexts using the Picovoice Console. Download the custom Porcupine keyword (.ppn) and Rhino context (.rhn) files and create an instance of Picovoice using the setKeywordPath and .setContextPath build methods.

Non-English Languages

Use the corresponding model file (.pv) to process non-English wake words and contexts. The model files for all supported languages are available on the Porcupine and Rhino GitHub repositories.

Pass in the Porcupine model file using the setPorcupineModelPath build method and the Rhino model file using the setRhinoModelPath to change the detection language:

Picovoice picovoice = new Picovoice.Builder()
                      .setAccessKey("${ACCESS_KEY}")
                      .setKeywordPath("${KEYWORD_FILE_PATH}")
                      .setWakeWordCallback(wakeWordCallback)
                      .setPorcupineModelPath("${MODEL_FILE_PATH}")
                      .setContextPath("${CONTEXT_FILE_PATH}")
                      .setInferenceCallback(inferenceCallback)
                      .setRhinoModelPath("${MODEL_FILE_PATH}")
                      .build();

Demo

For the Picovoice Java SDK, we offer demo applications that demonstrate how to use the end-to-end speech recognition engine on real-time audio streams (i.e. microphone input) and audio files.

Setup

1. Clone the Picovoice repository from GitHub:

git clone --recurse-submodules https://github.com/Picovoice/picovoice.git

2. Build the Picovoice Java demo using Gradle:

cd picovoice/demo/java
./gradlew build

Usage

To see the usage options for the demos, use the -h flag:

java -jar build/libs/picovoice-mic-demo.jar -h

Ensure you have a working microphone connected to your system and run the following command to make inferences based on the given keyword and context files:

java -jar build/libs/rhino-mic-demo.jar -a ${ACCESS_KEY} -k ${KEYWORD_FILE_PATH} -c ${CONTEXT_FILE_PATH}

For more information on our Picovoice demos for Java, head over to our GitHub repository.

Resources