Eagle Speaker Recognition
Node.js Quick Start

Platforms

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

Requirements

• Picovoice Account & AccessKey
• Node.js 16+
• npm

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 Node.js.

2. Install the eagle-node npm package:

npm install @picovoice/eagle-node

Usage

Speaker Enrollment

1. Create an instance of the profiler:

const { EagleProfiler } = require("@picovoice/eagle-node");

const accessKey = "${ACCESS_KEY}"; // Obtained from the Picovoice Console (https://console.picovoice.ai/)
const eagleProfiler = new EagleProfiler(accessKey);

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

const { EnrollProgress } = require("@picovoice/eagle-node");

function getAudioData(numSamples): Int16Array {
  // get audio frame of size `numSamples`
}

let percentage = 0;
while (percentage < 100) {
  const audioData = getAudioData(eagleProfiler.minEnrollSamples);

  const result: EnrollProgress = await eagleProfiler.enroll(audioData);
  if (result.feedback === EagleProfilerEnrollFeedback.NONE) {
    // audio is good!
  } else {
    // feedback code will tell you why audio was not used in enrollment
  }
  percentage = result.percentage;
}

3. Export the speaker profile:

const speakerProfile: Uint8Array = eagleProfiler.export();

4. Release the resources acquired by the profiler:

eagleProfiler.release();

Speaker Recognition

1. Create an instance of Eagle Speaker Recognition:

const { Eagle } = require("@picovoice/eagle-node");

const accessKey = "${ACCESS_KEY}"; // Obtained from the Picovoice Console (https://console.picovoice.ai/)
const eagle = new Eagle(accessKey, speakerProfile);

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

function getAudioData(numSamples): Int16Array {
  // get audio frame of size `numSamples`
}

while (true) {
  const audioData = getAudioData(eagle.frameLength);
  const scores: number[] = eagle.process(audioData);
}

3. Release the resources acquired by Eagle Speaker Recognition:

eagle.release()

Demos

For the Eagle Speaker Recognition SDK, we offer demo applications that demonstrate how to use the speaker recognition engine on real-time audio streams (i.e. microphone input) and audio files.

Setup

Install the Eagle Speaker Recognition demo package:

npm install -g @picovoice/eagle-node-demo

This package installs command-line utilities for the Eagle Speaker Recognition Node.js demos.

Usage

Use the --help flag to see the usage options for the demos:

eagle-mic-demo --help
eagle-file-demo --help

Speaker Enrollment & Recognition:

Ensure you have a working microphone connected to your system and run the command corresponding to your platform enroll speaker(s) and perform speaker recognition:

eagle-mic-demo --enroll --access_key ${ACCESS_KEY} --output_profile_path ${OUTPUT_PROFILE_PATH}

eagle-mic-demo --test --access_key ${ACCESS_KEY} --input_profile_paths ${INPUT_PROFILE_PATH_1, ...}

For more information on our Eagle Speaker Recognition demos for Node.js, head over to our GitHub repository.

Resources