On-device wake word detection powered by deep learning

Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

A lightweight, simple-to-use, RNN wake word listener

💬 /so.nus/ STT (speech to text) for Node with offline hotword detection

Deep learning for audio processing

ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!

This repository is a curated list of awesome Speech Keyword Spotting (Wake-Up Word Detection).

Code for Temporal Convolution for Real-time Keyword Spotting on Mobile Devices

Few-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus

Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.

wake word engine benchmark framework

Official implementation of the Keyword Transformer: https://arxiv.org/abs/2104.00769

[SLT'24] The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model

Wav2Keyword is keyword spotting(KWS) based on Wav2Vec 2.0. This model shows state-of-the-art in Speech commands dataset V1 and V2.

Learning Efficient Representations for Keyword Spotting with Triplet Loss

In this repository, we explore using a hybrid system consisting of a Convolutional Neural Network and a Support Vector Machine for Keyword Spotting task.

Classify audio with neural nets on embedded systems like the Raspberry Pi

Deep Learning for Speech

Official code for Long Expressive Memory (ICLR 2022, Spotlight)

Few-Shot Keyword Spotting