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Keyword Spotting

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

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Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 111–120 of 407 papers

Title	Date	Tasks	Status	Hype
Effective Combination of DenseNet andBiLSTM for Keyword Spotting	Jan 19, 2019	Keyword SpottingTime Series	—Unverified	0
Effective Integration of KAN for Keyword Spotting	Sep 13, 2024	Keyword SpottingKolmogorov-Arnold Networks	—Unverified	0
Efficient Continual Learning in Keyword Spotting using Binary Neural Networks	May 5, 2025	Continual LearningKeyword Spotting	—Unverified	0
Efficient dynamic filter for robust and low computational feature extraction	May 3, 2022	Keyword SpottingSpeaker Verification	—Unverified	0
Automatic Speech Recognition for Humanitarian Applications in Somali	Jul 23, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection	Jan 3, 2020	Keyword SpottingLine Detection	—Unverified	0
Efficient keyword spotting using time delay neural networks	Aug 28, 2018	Keyword SpottingTransfer Learning	—Unverified	0
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition	Jul 15, 2023	Anomaly DetectionKeyword Spotting	—Unverified	0
ELiRF at MediaEval 2014: Query by Example Search on Speech Task (QUESST)	Oct 16, 2014	Dynamic Time WarpingKeyword Spotting	—Unverified	0
CUNY Systems for the Query-by-Example Search on Speech Task at MediaEval 2015	Sep 14, 2015	Keyword Spotting	—Unverified	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