Eagle Speaker Recognition Engine
C Quick Start
Platforms
- Linux (x86_64)
- macOS (x86_64, arm64)
- Windows (x86_64)
- Raspberry Pi (3, 4, 5)
Requirements
Picovoice Account & AccessKey
Signup or Login to Picovoice Console to get your AccessKey
.
Make sure to keep your AccessKey
secret.
Overview
Eagle Speaker Recognition consists of 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 results in a 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
- Clone the repository:
Usage
- Include the public header files (
picovoice.h
andpv_eagle.h
). - Link the project to an appropriate precompiled library for the target platform and load it.
Speaker Enrollment
- Construct an instance of the profiler:
- Pass in audio to the
pv_eagle_profiler_enroll
function to enroll a speaker:
- Release resources explicitly when done with the profiler:
Speaker Recognition
- Construct an instance of the engine:
- Pass audio frames to the
pv_eagle_process
function to perform speaker recognition:
- Release resources explicitly when done with the engine:
Demo
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
- Clone the Eagle Speaker Recognition repository from GitHub using HTTPS:
- Build the microphone demo:
Usage
To see the usage options for the demo:
Ensure you have a working microphone connected to your system and run the command corresponding to your platform to either enroll a speaker or perform speaker recognition:
or
For more information on our Eagle Speaker Recognition demos for C, head over to our GitHub repository.