Keyword Spotting
96 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
WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit
wenet-e2e/wekws
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Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an indispensable component of smart devices.
Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the Input
nttcslab/m2d
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We propose a new method, Masked Modeling Duo (M2D), that learns representations directly while obtaining training signals using only masked patches.
Improving Label-Deficient Keyword Spotting Through Self-Supervised Pretraining
holgerbovbjerg/data2vec-kws
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This paper explores the effectiveness of SSL on small models for KWS and establishes that SSL can enhance the performance of small KWS models when labelled data is scarce.
SiDi KWS: A Large-Scale Multilingual Dataset for Keyword Spotting
Keyword spotting (KWS) has become a hot topic in speech processing due to the rise of commercial applications based on voice command detection, such as voice assistants.
IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languages
We hope IndicSUPERB contributes to the progress of developing speech language understanding models for Indian languages.
Keyword Spotting System and Evaluation of Pruning and Quantization Methods on Low-power Edge Microcontrollers
robobachelor/keyword-spotting-stm32
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The result also verified that the performance improvement for quantization and SIMD instruction.
Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource Devices
This work introduces BRILLsson, a novel binary neural network-based representation learning model for a broad range of non-semantic speech tasks.
Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting
In this paper, we propose a novel end-to-end user-defined keyword spotting method that utilizes linguistically corresponding patterns between speech and text sequences.
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark
We present our development experience and recent results for the MLPerf Tiny Inference Benchmark on field-programmable gate array (FPGA) platforms.
Avoid Overfitting User Specific Information in Federated Keyword Spotting
lxcnju/FedKWS-UI
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Federated KWS (FedKWS) could serve as a solution without directly sharing users' data.
