SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

Showing 101125 of 407 papers

TitleStatusHype
Building and benchmarking an Arabic Speech Commands dataset for small-footprint keyword spottingCode0
Hello Edge: Keyword Spotting on MicrocontrollersCode0
JavaScript Convolutional Neural Networks for Keyword Spotting in the Browser: An Experimental AnalysisCode0
Filler Word Detection and Classification: A Dataset and BenchmarkCode0
Boosting keyword spotting through on-device learnable user speech characteristicsCode0
Federated Learning for Keyword SpottingCode0
Audiomer: A Convolutional Transformer For Keyword SpottingCode0
ed-cec: improving rare word recognition using asr postprocessing based on error detection and context-aware error correctionCode0
End-to-end Keyword Spotting using Xception-1dCode0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
GTM-UVigo Systems for the Query-by-Example Search on Speech Task at MediaEval 2015Code0
Keyword localisation in untranscribed speech using visually grounded speech modelsCode0
Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and QuantizationCode0
Behavior of Keyword Spotting Networks Under Noisy Conditions0
An Alternative Deep Feature Approach to Line Level Keyword Spotting0
EmoAttack: Utilizing Emotional Voice Conversion for Speech Backdoor Attacks on Deep Speech Classification Models0
ELiRF at MediaEval 2015: Query by Example Search on Speech Task (QUESST)0
ELiRF at MediaEval 2014: Query by Example Search on Speech Task (QUESST)0
BBS-KWS:The Mandarin Keyword Spotting System Won the Video Keyword Wakeup Challenge0
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator0
Efficient keyword spotting using time delay neural networks0
Employing Phonetic Speech Recognition for Language and Dialect Specific Search0
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting0
Automating speech reception threshold measurements using automatic speech recognition0
Automatic Speech Recognition for Humanitarian Applications in Somali0
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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