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
Finite Element Analysis

FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin

Andreas D. 20 Jan 09, 2023
Code for the paper Hybrid Spectrogram and Waveform Source Separation

Demucs Music Source Separation This is the 3rd release of Demucs (v3), featuring hybrid source separation. For the waveform only Demucs (v2): Go this

Meta Research 4.8k Jan 04, 2023
CARL provides highly configurable contextual extensions to several well-known RL environments.

CARL (context adaptive RL) provides highly configurable contextual extensions to several well-known RL environments.

AutoML-Freiburg-Hannover 51 Dec 28, 2022
Distributed Arcface Training in Pytorch

Distributed Arcface Training in Pytorch

3 Nov 23, 2021
An introduction to satellite image analysis using Python + OpenCV and JavaScript + Google Earth Engine

A Gentle Introduction to Satellite Image Processing Welcome to this introductory course on Satellite Image Analysis! Satellite imagery has become a pr

Edward Oughton 32 Jan 03, 2023
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

mani 1.2k Jan 07, 2023
Garbage classification using structure data.

垃圾分类模型使用说明 1.包含以下数据文件 文件 描述 data/MaterialMapping.csv 物体以及其归类的信息 data/TestRecords 光谱原始测试数据 CSV 文件 data/TestRecordDesc.zip CSV 文件描述文件 data/Boundaries.cs

wenqi 1 Dec 10, 2021
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on

THUDM 176 Dec 17, 2022
O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning (CoRL 2021)

O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning Object-object Interaction Affordance Learning. For a given object-object int

Kaichun Mo 26 Nov 04, 2022
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a

Amazon 92 Jan 04, 2023
Sequence Modeling with Structured State Spaces

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

HazyResearch 896 Jan 01, 2023
Official implementation of paper "Query2Label: A Simple Transformer Way to Multi-Label Classification".

Introdunction This is the official implementation of the paper "Query2Label: A Simple Transformer Way to Multi-Label Classification". Abstract This pa

Shilong Liu 274 Dec 28, 2022
Koopman operator identification library in Python

pykoop pykoop is a Koopman operator identification library written in Python. It allows the user to specify Koopman lifting functions and regressors i

DECAR Systems Group 34 Jan 04, 2023
A PaddlePaddle implementation of STGCN with a few modifications in the model architecture in order to forecast traffic jam.

About This repository contains the code of a PaddlePaddle implementation of STGCN based on the paper Spatio-Temporal Graph Convolutional Networks: A D

Tianjian Li 1 Jan 11, 2022
🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

PyTorch implementation of OpenAI's Finetuned Transformer Language Model This is a PyTorch implementation of the TensorFlow code provided with OpenAI's

Hugging Face 1.4k Jan 05, 2023
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection

Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection Introduction This repository includes codes and models of "Effect of De

Amir Abbasi 5 Sep 05, 2022
The full training script for Enformer (Tensorflow Sonnet) on TPU clusters

Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt

Phil Wang 10 Oct 19, 2022
Simulation-based performance analysis of server-less Blockchain-enabled Federated Learning

Blockchain-enabled Server-less Federated Learning Repository containing the files used to reproduce the results of the publication "Blockchain-enabled

Francesc Wilhelmi 9 Sep 27, 2022
Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"

DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei

Sitao Xiang 24 May 16, 2022
For medical image segmentation

LeViT_UNet For medical image segmentation Our model is based on LeViT (https://github.com/facebookresearch/LeViT). You'd better gitclone its codes. Th

13 Dec 24, 2022