SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

Showing 226250 of 407 papers

TitleStatusHype
Feature learning for efficient ASR-free keyword spotting in low-resource languages0
Text Anchor Based Metric Learning for Small-footprint Keyword Spotting0
Bifocal Neural ASR: Exploiting Keyword Spotting for Inference Optimization0
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers0
Multi-task Learning with Cross Attention for Keyword Spotting0
AUC Optimization for Robust Small-footprint Keyword Spotting with Limited Training Data0
An Integrated Framework for Two-pass Personalized Voice Trigger0
PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation0
Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis0
Zero-Shot Federated Learning with New Classes for Audio Classification0
MLPerf Tiny BenchmarkCode1
Broadcasted Residual Learning for Efficient Keyword SpottingCode1
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting0
Teaching keyword spotters to spot new keywords with limited examples0
Noisy student-teacher training for robust keyword spotting0
A Streaming End-to-End Framework For Spoken Language Understanding0
Wav2KWS: Transfer Learning from Speech Representations for Keyword SpottingCode1
Building and benchmarking an Arabic Speech Commands dataset for small-footprint keyword spottingCode0
Efficient Keyword Spotting by capturing long-range interactions with Temporal Lambda NetworksCode0
End-to-end Keyword Spotting using Neural Architecture Search and Quantization0
The DKU System Description for The Interspeech 2021 Auto-KWS Challenge0
A Probabilistic Framework for Lexicon-based Keyword Spotting in Handwritten Text Images0
AST: Audio Spectrogram TransformerCode2
Few-Shot Keyword Spotting in Any LanguageCode1
PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification0
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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