SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

Showing 176200 of 407 papers

TitleStatusHype
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training0
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation0
Improving Small Footprint Few-shot Keyword Spotting with Supervision on Auxiliary Data0
CUHK System for QUESST Task of MediaEval 20140
Implicit Acoustic Echo Cancellation for Keyword Spotting and Device-Directed Speech Detection0
台語關鍵詞辨識之實作與比較 (Implementation and Comparison of Keyword Spotting for Taiwanese) [In Chinese]0
CTC-aligned Audio-Text Embedding for Streaming Open-vocabulary Keyword Spotting0
iPhonMatchNet: Zero-Shot User-Defined Keyword Spotting Using Implicit Acoustic Echo Cancellation0
IIIT-H System for MediaEval 2014 QUESST0
Keyword-Guided Adaptation of Automatic Speech Recognition0
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting0
How Tiny Can Analog Filterbank Features Be Made for Ultra-low-power On-device Keyword Spotting?0
Keyword spotting -- Detecting commands in speech using deep learning0
Keyword spotting for audiovisual archival search in Uralic languages0
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers0
Convexity-based Pruning of Speech Representation Models0
A Probabilistic Framework for Lexicon-based Keyword Spotting in Handwritten Text Images0
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts0
Contrastive Learning With Audio Discrimination For Customizable Keyword Spotting In Continuous Speech0
Latency Control for Keyword Spotting0
Learnable Front Ends Based on Temporal Modulation for Music Tagging0
Hierarchical Neural Network Architecture In Keyword Spotting0
Contrastive Augmentation: An Unsupervised Learning Approach for Keyword Spotting in Speech Technology0
Application of Knowledge Distillation to Multi-task Speech Representation Learning0
HEiMDaL: Highly Efficient Method for Detection and Localization of wake-words0
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Benchmark Results

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