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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 101–125 of 407 papers

TitleStatusHype
DASB -- Discrete Audio and Speech Benchmark—0
Disentangled Training with Adversarial Examples For Robust Small-footprint Keyword Spotting—0
Does Single-channel Speech Enhancement Improve Keyword Spotting Accuracy? A Case Study—0
AUC Optimization for Robust Small-footprint Keyword Spotting with Limited Training Data—0
DONUT: CTC-based Query-by-Example Keyword Spotting—0
Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spotting—0
Dynamic curriculum learning via data parameters for noise robust keyword spotting—0
Always-On, Sub-300-nW, Event-Driven Spiking Neural Network based on Spike-Driven Clock-Generation and Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device—0
Dark Experience for Incremental Keyword Spotting—0
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition—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
Automatic Speech Recognition for Humanitarian Applications in Somali—0
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection—0
Efficient keyword spotting using time delay neural networks—0
CUNY Systems for the Query-by-Example Search on Speech Task at MediaEval 2015—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
ASAP-FE: Energy-Efficient Feature Extraction Enabling Multi-Channel Keyword Spotting on Edge Processors—0
A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons—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