On-device wake word detection powered by deep learning
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Updated
Jul 5, 2024 - Python
On-device wake word detection powered by deep learning
A lightweight, simple-to-use, RNN wake word listener
Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".
Deep learning for audio processing
💬 /so.nus/ STT (speech to text) for Node with offline hotword detection
Code for Temporal Convolution for Real-time Keyword Spotting on Mobile Devices
This repository is a curated list of awesome Speech Keyword Spotting (Wake-Up Word Detection).
Few-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus
Official implementation of the Keyword Transformer: https://arxiv.org/abs/2104.00769
Wav2Keyword is keyword spotting(KWS) based on Wav2Vec 2.0. This model shows state-of-the-art in Speech commands dataset V1 and V2.
wake word engine benchmark framework
Train a 4-layer Convolutional Neural Network to detect trigger word
In this repository, we explore using a hybrid system consisting of a Convolutional Neural Network and a Support Vector Machine for Keyword Spotting task.
Few-Shot Keyword Spotting
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!
Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
Learning Efficient Representations for Keyword Spotting with Triplet Loss
Classify audio with neural nets on embedded systems like the Raspberry Pi
Won't it be cool to build a speech assistant like Alexa or Siri yourself without voice API and network connection?
BC-ResNet for Keyword Spotting
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