SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 376–400 of 407 papers

TitleStatusHype
EdgeCRNN: an edgecomputing oriented model of acoustic feature enhancement for keyword spotting—0
Effective Combination of DenseNet andBiLSTM for Keyword Spotting—0
Effective Integration of KAN for Keyword Spotting—0
Efficient Continual Learning in Keyword Spotting using Binary Neural Networks—0
Efficient dynamic filter for robust and low computational feature extraction—0
Efficient keyword spotting using time delay neural networks—0
ELiRF at MediaEval 2014: Query by Example Search on Speech Task (QUESST)—0
ELiRF at MediaEval 2015: Query by Example Search on Speech Task (QUESST)—0
EmoAttack: Utilizing Emotional Voice Conversion for Speech Backdoor Attacks on Deep Speech Classification Models—0
Employing Phonetic Speech Recognition for Language and Dialect Specific Search—0
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting—0
End-to-end Keyword Spotting using Neural Architecture Search and Quantization—0
End-to-End Streaming Keyword Spotting—0
End-to-End User-Defined Keyword Spotting using Shifted Delta Coefficients—0
Enhancing Few-shot Keyword Spotting Performance through Pre-Trained Self-supervised Speech Models—0
Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis—0
Eventprop training for efficient neuromorphic applications—0
Expanding the Range of Automatic Emotion Detection in Microblogging Text—0
Exploring Filterbank Learning for Keyword Spotting—0
Exploring Representation Learning for Small-Footprint Keyword Spotting—0
Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting—0
Exploring the Boundaries of On-Device Inference: When Tiny Falls Short, Go Hierarchical—0
Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring—0
Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders—0
Feature learning for efficient ASR-free keyword spotting in low-resource languages—0
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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