Picovoice Eagle - Speaker Recognition Benchmark

Prerequisites

• Ubuntu 22.04 (x86_64)
• Git
• Python 3.7+
• PIP
• Picovoice Console Account

Usage

1. Clone the repository:

git clone https://github.com/Picovoice/speaker-recognition-benchmark.git

2. Install the dependencies:

pip3 install -r requirements.txt

3. Set up the dataset as described in the main readme of the repository.

4. Run the benchmark:

python3 benchmark.py \
    --type {ACCURACY|CPU} \
    --dataset ${DATASET} \
    --data-folder ${DATA_FOLDER} \
    --label-folder ${LABEL_FOLDER} \
    --engine PICVOICE_EAGLE \
    --picovoice-access-key ${PICOVOICE_ACCESS_KEY}

Where:

• type is the type of benchmark to run. It can be ACCURACY or CPU.
• dataset is the name of the dataset to use.
• data-folder is the path to the folder containing the audio files.
• label-folder is the path to the folder containing the label files.
• picovoice-access-key is the AccessKey obtained from Picovoice Console.