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Keyword Spotting

In speech processing, keyword spotting deals with the identification of keywords in utterances.

( Image credit: Simon Grest )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 171–180 of 407 papers

Title	Date	Tasks	Status	Hype	Score
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training	Jul 6, 2019	Acoustic ModellingAutomatic Speech Recognition	—Unverified	0	0
CUHK System for QUESST Task of MediaEval 2014	Oct 16, 2014	ClusteringDynamic Time Warping	—Unverified	0	0
Implicit Acoustic Echo Cancellation for Keyword Spotting and Device-Directed Speech Detection	Nov 20, 2021	Acoustic echo cancellationKeyword Spotting	—Unverified	0	0
台語關鍵詞辨識之實作與比較 (Implementation and Comparison of Keyword Spotting for Taiwanese) [In Chinese]	Sep 1, 2012	Keyword Spotting	—Unverified	0	0
CTC-aligned Audio-Text Embedding for Streaming Open-vocabulary Keyword Spotting	Jun 12, 2024	Keyword Spotting	—Unverified	0	0
IIIT-H System for MediaEval 2014 QUESST	Oct 16, 2014	Dynamic Time WarpingKeyword Spotting	—Unverified	0	0
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation	Jul 9, 2019	BIG-bench Machine LearningKeyword Spotting	—Unverified	0	0
Improving Small Footprint Few-shot Keyword Spotting with Supervision on Auxiliary Data	Aug 31, 2023	Keyword SpottingMulti-Task Learning	—Unverified	0	0
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting	Mar 15, 2017	Keyword SpottingSmall-Footprint Keyword Spotting	—Unverified	0	0
How Tiny Can Analog Filterbank Features Be Made for Ultra-low-power On-device Keyword Spotting?	Apr 17, 2023	Keyword Spotting	—Unverified	0	0

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All datasets QUESST Google Speech Commands hey Siri FKD Google Speech Commands V2 35 TensorFlow VoxForge Google Speech Commands (v2)Google Speech Commands V2 12

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	NNI non-filtered(for the development set)	Cnxe	6.09	—	Unverified
2	NNI Choi(for the development set)	Cnxe	5.89	—	Unverified
3	NTU rnn (eval)	Cnxe	2.01	—	Unverified
4	NTU dtw (eval)	Cnxe	2.01	—	Unverified
5	NTU dtw (dev)	Cnxe	2.01	—	Unverified
6	NTU rnn (dev)	Cnxe	2.01	—	Unverified
7	ELiRF SDTW (eval)	Cnxe	1.19	—	Unverified
8	ELiRF SDTW-avg (eval)	Cnxe	1.07	—	Unverified
9	ELiRF SDTW (dev)	Cnxe	1.07	—	Unverified
10	CUNY [Subseq+MFCC] (eval)	Cnxe	1.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	WaveFormer	Google Speech Commands V2 12	98.8	—	Unverified
2	QNN	Google Speech Commands V2 35	98.6	—	Unverified
3	TripletLoss-res15	Google Speech Commands V1 12	98.56	—	Unverified
4	M2D	Google Speech Commands V2 35	98.5	—	Unverified
5	EAT-S	Google Speech Commands V2 35	98.15	—	Unverified
6	Audio Spectrogram Transformer	Google Speech Commands V2 35	98.11	—	Unverified
7	EdgeCRNN 2.0×	Google Speech Commands V2 12	98.05	—	Unverified
8	BC-ResNet-8	Google Speech Commands V1 12	98	—	Unverified
9	HTS-AT	Google Speech Commands V2 35	98	—	Unverified
10	Wav2KWS	Google Speech Commands V1 12	97.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Stacked 1D CNN	Error Rate	1.99	—	Unverified
2	End-to-end DNN-HMM	Error Rate	1.7	—	Unverified
3	HEiMDaL	Error Rate	0.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Res26	Accuracy	95.88	—	Unverified
2	EfficientNet-A0 + SA + TL	Accuracy	95.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	QuaternionNeuralNetwork	Accuracy (10-fold)	98.53	—	Unverified
2	SSAMBA	Accuracy (10-fold)	97.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TensorFlow's model version 2	TFMA	89.7	—	Unverified
2	TensorFlow's model version 1	TFMA	85.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	2D-ConvNet	Accuracy (%)	95.4	—	Unverified
2	1D-ConvNet	Accuracy (%)	93.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Quaternion Neural Networks	Accuracy(10-fold)	98.53	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MicroNet-KWS-L	Accuracy	95.3	—	Unverified