SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

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Showing 351–400 of 407 papers

TitleStatusHype
Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase—0
Spoken Language Identification using ConvNets—0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
Honkling: In-Browser Personalization for Ubiquitous Keyword SpottingCode0
Keyword Spotting Simplified: A Segmentation-Free Approach using Character Counting and CTC re-scoringCode0
Stochastic Adaptive Neural Architecture Search for Keyword SpottingCode0
End-to-end Keyword Spotting using Xception-1dCode0
Efficient keyword spotting using dilated convolutions and gatingCode0
Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword SpottingCode0
Building and benchmarking an Arabic Speech Commands dataset for small-footprint keyword spottingCode0
Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the InputCode0
Keyword localisation in untranscribed speech using visually grounded speech modelsCode0
Semi-Supervised Federated Learning for Keyword SpottingCode0
AraSpot: Arabic Spoken Command SpottingCode0
Efficient Keyword Spotting by capturing long-range interactions with Temporal Lambda NetworksCode0
An Investigation of Few-Shot Learning in Spoken Term ClassificationCode0
What’s Cookin’? Interpreting Cooking Videos using Text, Speech and VisionCode0
Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-ConvolutionsCode0
Hello Edge: Keyword Spotting on MicrocontrollersCode0
JavaScript Convolutional Neural Networks for Keyword Spotting in the Browser: An Experimental AnalysisCode0
Integrated Parameter-Efficient Tuning for General-Purpose Audio ModelsCode0
What's Cookin'? Interpreting Cooking Videos using Text, Speech and VisionCode0
Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wildCode0
ImportantAug: a data augmentation agent for speechCode0
GTM-UVigo Systems for the Query-by-Example Search on Speech Task at MediaEval 2015Code0
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
The NPU System for the 2020 Personalized Voice Trigger ChallengeCode0
Audio Explanation Synthesis with Generative Foundation ModelsCode0
DONUT: CTC-based Query-by-Example Keyword SpottingCode0
Learning Delays Through Gradients and Structure: Emergence of Spatiotemporal Patterns in Spiking Neural NetworksCode0
Filler Word Detection and Classification: A Dataset and BenchmarkCode0
Advances in Small-Footprint Keyword Spotting: A Comprehensive Review of Efficient Models and AlgorithmsCode0
Boosting keyword spotting through on-device learnable user speech characteristicsCode0
Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource DevicesCode0
Trainable Frontend For Robust and Far-Field Keyword SpottingCode0
TACos: Learning Temporally Structured Embeddings for Few-Shot Keyword Spotting with Dynamic Time WarpingCode0
Temporal Convolution for Real-time Keyword Spotting on Mobile DevicesCode0
Temporal Feedback Convolutional Recurrent Neural Networks for Speech Command RecognitionCode0
Attention-based End-to-End Models for Small-Footprint Keyword SpottingCode0
Federated Learning for Keyword SpottingCode0
Neural ODE with Temporal Convolution and Time Delay Neural Networks for Small-Footprint Keyword SpottingCode0
Neuromorphic Keyword Spotting with Pulse Density Modulation MEMS MicrophonesCode0
READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival DocumentsCode0
Benchmarking Keyword Spotting Efficiency on Neuromorphic HardwareCode0
Noise-Robust Keyword Spotting through Self-supervised PretrainingCode0
Tiny, always-on and fragile: Bias propagation through design choices in on-device machine learning workflowsCode0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
Adversarial Example Detection by Classification for Deep Speech RecognitionCode0
What is Learnt by the LEArnable Front-end (LEAF)? Adapting Per-Channel Energy Normalisation (PCEN) to Noisy ConditionsCode0
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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