Keyword Spotting
95 papers with code • 10 benchmarks • 8 datasets
In speech processing, keyword spotting deals with the identification of keywords in utterances.
( Image credit: Simon Grest )
Benchmarks
These leaderboards are used to track progress in Keyword Spotting
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Libraries
Use these libraries to find Keyword Spotting models and implementationsDatasets
Speech Commands
TAU Urban Acoustic Scenes 2019
VoxForge
PodcastFillers
EmoSpeech
Latest papers with no code
TDT-KWS: Fast And Accurate Keyword Spotting Using Token-and-duration Transducer
Designing an efficient keyword spotting (KWS) system that delivers exceptional performance on resource-constrained edge devices has long been a subject of significant attention.
More than words: Advancements and challenges in speech recognition for singing
This paper addresses the challenges and advancements in speech recognition for singing, a domain distinctly different from standard speech recognition.
Boosting keyword spotting through on-device learnable user speech characteristics
Keyword spotting systems for always-on TinyML-constrained applications require on-site tuning to boost the accuracy of offline trained classifiers when deployed in unseen inference conditions.
On-Device Domain Learning for Keyword Spotting on Low-Power Extreme Edge Embedded Systems
Keyword spotting accuracy degrades when neural networks are exposed to noisy environments.
A Closer Look at Wav2Vec2 Embeddings for On-Device Single-Channel Speech Enhancement
Self-supervised learned models have been found to be very effective for certain speech tasks such as automatic speech recognition, speaker identification, keyword spotting and others.
Multilingual acoustic word embeddings for zero-resource languages
This research addresses the challenge of developing speech applications for zero-resource languages that lack labelled data.
Contrastive Learning With Audio Discrimination For Customizable Keyword Spotting In Continuous Speech
Furthermore, experiments on the continuous speech dataset LibriSpeech demonstrate that, by incorporating audio discrimination, CLAD achieves significant performance gain over CL without audio discrimination.
Maximum-Entropy Adversarial Audio Augmentation for Keyword Spotting
Data augmentation is a key tool for improving the performance of deep networks, particularly when there is limited labeled data.
U2-KWS: Unified Two-pass Open-vocabulary Keyword Spotting with Keyword Bias
Open-vocabulary keyword spotting (KWS), which allows users to customize keywords, has attracted increasingly more interest.
Keyword spotting -- Detecting commands in speech using deep learning
Speech recognition has become an important task in the development of machine learning and artificial intelligence.
