Eagle Speaker Recognition
Android Quick Start

Platforms

• Android (5.0+, API 21+)

Requirements

• Picovoice Account and AccessKey
• Android Studio
• Android device with USB debugging enabled or Android simulator

Picovoice Account & AccessKey

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

Overview

Eagle Speaker Recognition has two distinct steps: Enrollment and Recognition. In the enrollment step, Eagle analyzes a series of utterances from a particular speaker to learn their unique voiceprint. This step produces an Eagle Profile object, which can be stored and utilized during inference. During the Recognition step, Eagle compares the incoming frames of audio to the voiceprints of all enrolled speakers in real-time to determine the similarity between them.

Quick Start

Setup

1. Install Android Studio.

2. Include mavenCentral() repository in the top-level build.gradle. Then add the following to the app's build.gradle:

dependencies {
    // ...
    implementation 'ai.picovoice:eagle-android:${LATEST_VERSION}' // replace with latest version
}

3. Add the following to the app's AndroidManifest.xml file to enable recording with an Android device's microphone:

<uses-permission android:name="android.permission.INTERNET" />
<uses-permission android:name="android.permission.RECORD_AUDIO" />

Usage

Speaker Enrollment

1. Create an instance of the profiler:

import ai.picovoice.eagle.*;

final String accessKey = "${ACCESS_KEY}";

try {
    EagleProfiler eagleProfiler = new EagleProfiler.Builder()
            .setAccessKey(accessKey)
            .build();
} catch (EagleException e) { }

2. Pass the enrollment audio data to the profiler until the enrollment percentage reaches 100%:

public short[] getNextEnrollAudioData() {
    // get audio data
}

EagleProfilerEnrollFeedback feedback = null;
try {
    while (feedback != null && feedback.getPercentage() < 100.0) {
        feedback = eagleProfiler.enroll(getNextEnrollAudioData());
    }
} catch (EagleException e) { }

3. Export the speaker profile:

try {
    EagleProfile speakerProfile = eagleProfiler.export();
} catch (EagleException e) { }

4. Release the resources acquired by the profiler:

eagleProfiler.delete();

Speaker Recognition

1. Create an instance of Eagle Speaker Recognition:

import ai.picovoice.eagle.*;

final String accessKey = "${ACCESS_KEY}";

try {
    Eagle eagle = new Eagle.Builder()
        .setAccessKey(accessKey)
        .setSpeakerProfile(speakerProfile)
        .build();
} catch (EagleException e) { }

2. Pass the incoming audio stream to Eagle Speaker Recognition:

public short[] getNextAudioFrame() {
    // get audio frame    
}

try {
    while (true) {
        float[] scores = eagle.process(getNextAudioFrame());
    }
} catch (EagleException e) { }

3. Release the resources acquired by Eagle Speaker Recognition:

eagle.delete()

Demos

For the Eagle Speaker Recognition Android SDK, we offer demo applications that demonstrate how to use the speaker recognition engine on real-time audio streams.

Setup

Clone the Eagle Speaker Recognition repository from GitHub using HTTPS:

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

Usage

1. Open the Android demo using Android Studio.
2. Copy your AccessKey from Picovoice Console into the ACCESS_KEY variable in MainActivity.java.
3. Run the application using a connected Android device or using an Android simulator.

Resources