Eagle Speaker Recognition
Python Quick Start

Platforms

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

Requirements

• Picovoice Account & AccessKey
• Python 3.9+
• PIP

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 Python 3 (3.7 or higher).

2. Install the pveagle Python package using PIP:

pip3 install pveagle

Usage

Speaker Enrollment

1. Create an instance of the profiler:

import pveagle

access_key = "${ACCESS_KEY}"
eagle_profiler = pveagle.create_profiler(access_key)

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

def get_next_enroll_audio_data(num_samples):
    pass


percentage = 0.0
while percentage < 100.0:
    percentage, feedback = eagle_profiler.enroll(get_next_enroll_audio_data(eagle_profiler.min_enroll_samples))
    print(feedback.name)

3. Export the speaker profile:

speaker_profile = eagle_profiler.export()

4. Release the resources acquired by the profiler:

eagle_profiler.delete()

Speaker Recognition

1. Create an instance of Eagle Speaker Recognition:

eagle = pveagle.create_recognizer(access_key, speaker_profile)

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

def get_next_audio_frame():
    pass


while True:
    score = eagle.process(get_next_audio_frame())

3. Release the resources acquired by Eagle Speaker Recognition:

eagle.delete()

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 pveagledemo Python package using PIP:

pip3 install pveagledemo

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

Usage

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

eagle_demo_mic --help
eagle_demo_file --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_demo_mic enroll --access_key ${ACCESS_KEY} --output_profile_path ${OUTPUT_PROFILE_PATH}

eagle_demo_mic test --access_key ${ACCESS_KEY} --input_profile_paths ${INPUT_PROFILE_PATH}

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

Resources