Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

Overview

Keyword Spotting Transformer

This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train on the 35 words speech command dataset

Paper : Keyword Transformer: A Self-Attention Model for Keyword Spotting

Model architecture

alt text

Download the dataset

To download the dataset use the following command

wget https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz
mkdir data
mv ./speech_commands_v0.02.tar.gz ./data
cd ./data
tar -xf ./speech_commands_v0.02.tar.gz
cd ../

Setup virtual environment

virtualenv -p python3 venv
source ./venv/bin/activate

Install dependencies

pip install -r requirements.txt

Training the model

To train the model run this command

python3 train.py --data_dir ${Path to data directory} \
                 --logdir ${Path to log directory} \
                 --num_layers ${Number of sequential encoder layers} \
                 --d_model ${Dimension of the encoder layers} \
                 --num_heads ${Number of heads in multi head attention layer} \
                 --mlp_dim ${Dimension of mlp layers} \
                 --lr ${Learning rate} \
                 --weight_decay ${Weight decay} \
                 --batch_size ${Batch size} \
                 --epochs ${Number of epochs} \
                 --save_dir ${Directory to save the model weights}

To track your training metrics

tensorboard --logdir  ${Path to log directory}

Predicting keyword of audio file

To predict the keyword of the audio file

python3 test.py --model_dir ${Saved model directory} \
                --file_path ${Audio file}
Owner
Intelligent Machines Limited
#AIforGood
Intelligent Machines Limited
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