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 76–100 of 407 papers

TitleStatusHype
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
0/1 Deep Neural Networks via Block Coordinate Descent—0
A Literature Review of Keyword Spotting Technologies for Urdu—0
AUC Optimization for Robust Small-footprint Keyword Spotting with Limited Training Data—0
Adaptive Noise Resilient Keyword Spotting Using One-Shot Learning—0
EdgeCRNN: an edgecomputing oriented model of acoustic feature enhancement for keyword spotting—0
A Joint Model of Orthography and Morphological Segmentation—0
AdaKWS: Towards Robust Keyword Spotting with Test-Time Adaptation—0
AI-Powered Agile Analog Circuit Design and Optimization—0
Deep Spoken Keyword Spotting: An Overview—0
DeltaKWS: A 65nm 36nJ/Decision Bio-inspired Temporal-Sparsity-Aware Digital Keyword Spotting IC with 0.6V Near-Threshold SRAM—0
Dynamic curriculum learning via data parameters for noise robust keyword spotting—0
Efficient Continual Learning in Keyword Spotting using Binary Neural Networks—0
Assessing the Impact of Anisotropy in Neural Representations of Speech: A Case Study on Keyword Spotting—0
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting—0
Data Augmentation for Robust Keyword Spotting under Playback Interference—0
ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages—0
Bonseyes AI Pipeline -- bringing AI to you. End-to-end integration of data, algorithms and deployment tools—0
Deep Convolutional Spiking Neural Networks for Keyword Spotting—0
DASB -- Discrete Audio and Speech Benchmark—0
Dark Experience for Incremental Keyword Spotting—0
Delta Keyword Transformer: Bringing Transformers to the Edge through Dynamically Pruned Multi-Head Self-Attention—0
A Streaming End-to-End Framework For Spoken Language Understanding—0
Developing Far-Field Speaker System Via Teacher-Student Learning—0
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition—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