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
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

ZJU-VIPA 47 Jan 09, 2023
Code for the AI lab course 2021/2022 of the University of Verona

AI-Lab Code for the AI lab course 2021/2022 of the University of Verona Set-Up the environment for the curse Download Anaconda for your System. Instal

Davide Corsi 5 Oct 19, 2022
Yet another video caption

Yet another video caption

Fan Zhimin 5 May 26, 2022
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks

FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks

HKBU High Performance Machine Learning Lab 6 Nov 18, 2022
SynNet - synthetic tree generation using neural networks

SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s

Wenhao Gao 60 Dec 29, 2022
Main Results on ImageNet with Pretrained Models

This repository contains Pytorch evaluation code, training code and pretrained models for the following projects: SPACH (A Battle of Network Structure

Microsoft 151 Dec 14, 2022
AFLFast (extends AFL with Power Schedules)

AFLFast Power schedules implemented by Marcel Böhme [email protected]

Marcel Böhme 380 Jan 03, 2023
[ECCV 2020] Gradient-Induced Co-Saliency Detection

Gradient-Induced Co-Saliency Detection Zhao Zhang*, Wenda Jin*, Jun Xu, Ming-Ming Cheng ⭐ Project Home » The official repo of the ECCV 2020 paper Grad

Zhao Zhang 35 Nov 25, 2022
A lightweight python AUTOmatic-arRAY library.

A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a

Johnnie Gray 62 Dec 27, 2022
ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

Martin Huber 59 Dec 09, 2022
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

Data Analytics and Machine Learning Group 124 Dec 30, 2022
LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection.

LightLog Introduction LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection. Function description [BG

25 Dec 17, 2022
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.

Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count

46 Dec 03, 2022
A Pytorch implementation of CVPR 2021 paper "RSG: A Simple but Effective Module for Learning Imbalanced Datasets"

RSG: A Simple but Effective Module for Learning Imbalanced Datasets (CVPR 2021) A Pytorch implementation of our CVPR 2021 paper "RSG: A Simple but Eff

120 Dec 12, 2022
Code release of paper Improving neural implicit surfaces geometry with patch warping

NeuralWarp: Improving neural implicit surfaces geometry with patch warping Project page | Paper Code release of paper Improving neural implicit surfac

François Darmon 167 Dec 30, 2022
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"

SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P

Gi-Cheon Kang 9 Jul 05, 2022
Official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021.

Introduction This repository is the official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021. Data-free Kno

NVIDIA Research Projects 50 Jan 05, 2023
Deep Learning for Time Series Forecasting.

nixtlats:Deep Learning for Time Series Forecasting [nikstla] (noun, nahuatl) Period of time. State-of-the-art time series forecasting for pytorch. Nix

Nixtla 5 Dec 06, 2022
[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

EPCDepth EPCDepth is a self-supervised monocular depth estimation model, whose supervision is coming from the other image in a stereo pair. Details ar

Rui Peng 110 Dec 23, 2022
Codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing

Contrast and Mix (CoMix) The repository contains the codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Backgroun

Computer Vision and Intelligence Research (CVIR) 13 Dec 10, 2022