SOTAVerified

Spoken Command Recognition

Papers

Showing 110 of 10 papers

TitleStatusHype
SSAST: Self-Supervised Audio Spectrogram TransformerCode2
ATST: Audio Representation Learning with Teacher-Student TransformerCode1
Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command RecognitionCode1
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer0
A Quantum Kernel Learning Approach to Acoustic Modeling for Spoken Command Recognition0
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition0
Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech ProcessingCode0
Exploiting Hybrid Models of Tensor-Train Networks for Spoken Command Recognition0
Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks0
Contrastive Learning of General-Purpose Audio RepresentationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SSAST-FRAMEAccuracy98.1Unverified
2Base (ours)Accuracy98Unverified
3SSAST-PATCHAccuracy98Unverified
4COLAAccuracy95.5Unverified