SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

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Showing 1–25 of 407 papers

TitleStatusHype
PaddleSpeech: An Easy-to-Use All-in-One Speech ToolkitCode6
GLAP: General contrastive audio-text pretraining across domains and languagesCode2
MFA-KWS: Effective Keyword Spotting with Multi-head Frame-asynchronous DecodingCode2
Streaming Keyword Spotting Boosted by Cross-layer Discrimination ConsistencyCode2
SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space ModelCode2
TDT-KWS: Fast And Accurate Keyword Spotting Using Token-and-duration TransducerCode2
WeKws: A production first small-footprint end-to-end Keyword Spotting ToolkitCode2
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and DetectionCode2
SSAST: Self-Supervised Audio Spectrogram TransformerCode2
AST: Audio Spectrogram TransformerCode2
Training Keyword Spotters with Limited and Synthesized Speech DataCode2
Chameleon: A MatMul-Free Temporal Convolutional Network Accelerator for End-to-End Few-Shot and Continual Learning from Sequential DataCode1
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African LanguagesCode1
Self-Learning for Personalized Keyword Spotting on Ultra-Low-Power Audio SensorsCode1
Text-aware Speech Separation for Multi-talker Keyword SpottingCode1
ED-sKWS: Early-Decision Spiking Neural Networks for Rapid,and Energy-Efficient Keyword SpottingCode1
MM-KWS: Multi-modal Prompts for Multilingual User-defined Keyword SpottingCode1
Sparse Binarization for Fast Keyword SpottingCode1
The taste of IPA: Towards open-vocabulary keyword spotting and forced alignment in any languageCode1
Towards on-Device Keyword Spotting using Low-Footprint Quaternion Neural ModelsCode1
PhonMatchNet: Phoneme-Guided Zero-Shot Keyword Spotting for User-Defined KeywordsCode1
Few-Shot Open-Set Learning for On-Device Customization of KeyWord Spotting SystemsCode1
Reduced Precision Floating-Point Optimization for Deep Neural Network On-Device Learning on MicroControllersCode1
LipLearner: Customizable Silent Speech Interactions on Mobile DevicesCode1
ASiT: Local-Global Audio Spectrogram vIsion Transformer for Event ClassificationCode1
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All datasetsQUESSTGoogle Speech Commandshey SiriFKDGoogle Speech Commands V2 35TensorFlowVoxForgeGoogle Speech Commands (v2)Google Speech Commands V2 12

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NNI non-filtered(for the development set)Cnxe6.09—Unverified
2NNI Choi(for the development set)Cnxe5.89—Unverified
3NTU rnn (eval)Cnxe2.01—Unverified
4NTU dtw (eval)Cnxe2.01—Unverified
5NTU dtw (dev)Cnxe2.01—Unverified
6NTU rnn (dev)Cnxe2.01—Unverified
7ELiRF SDTW (eval)Cnxe1.19—Unverified
8ELiRF SDTW-avg (eval)Cnxe1.07—Unverified
9ELiRF SDTW (dev)Cnxe1.07—Unverified
10CUNY [Subseq+MFCC] (eval)Cnxe1.07—Unverified
#ModelMetricClaimedVerifiedStatus
1WaveFormerGoogle Speech Commands V2 1298.8—Unverified
2QNNGoogle Speech Commands V2 3598.6—Unverified
3TripletLoss-res15Google Speech Commands V1 1298.56—Unverified
4M2DGoogle Speech Commands V2 3598.5—Unverified
5EAT-SGoogle Speech Commands V2 3598.15—Unverified
6Audio Spectrogram TransformerGoogle Speech Commands V2 3598.11—Unverified
7EdgeCRNN 2.0×Google Speech Commands V2 1298.05—Unverified
8BC-ResNet-8Google Speech Commands V1 1298—Unverified
9HTS-ATGoogle Speech Commands V2 3598—Unverified
10Wav2KWSGoogle Speech Commands V1 1297.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Stacked 1D CNNError Rate1.99—Unverified
2End-to-end DNN-HMMError Rate1.7—Unverified
3HEiMDaLError Rate0.45—Unverified
#ModelMetricClaimedVerifiedStatus
1Res26Accuracy95.88—Unverified
2EfficientNet-A0 + SA + TLAccuracy95.83—Unverified
#ModelMetricClaimedVerifiedStatus
1QuaternionNeuralNetworkAccuracy (10-fold)98.53—Unverified
2SSAMBAAccuracy (10-fold)97.4—Unverified
#ModelMetricClaimedVerifiedStatus
1TensorFlow's model version 2TFMA89.7—Unverified
2TensorFlow's model version 1TFMA85.4—Unverified
#ModelMetricClaimedVerifiedStatus
12D-ConvNetAccuracy (%)95.4—Unverified
21D-ConvNetAccuracy (%)93.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Quaternion Neural NetworksAccuracy(10-fold)98.53—Unverified
#ModelMetricClaimedVerifiedStatus
1MicroNet-KWS-LAccuracy95.3—Unverified