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 201–250 of 407 papers

TitleStatusHype
A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting—0
Keyword localisation in untranscribed speech using visually grounded speech modelsCode0
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and DetectionCode2
Progressive Continual Learning for Spoken Keyword SpottingCode1
Tiny, always-on and fragile: Bias propagation through design choices in on-device machine learning workflowsCode0
ImportantAug: a data augmentation agent for speechCode0
BBS-KWS:The Mandarin Keyword Spotting System Won the Video Keyword Wakeup Challenge—0
Phone Based Keyword Spotting for Transcribing Very Low Resource Languages—0
Implicit Acoustic Echo Cancellation for Keyword Spotting and Device-Directed Speech Detection—0
Deep Spoken Keyword Spotting: An Overview—0
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator—0
Ultra-Low Power Keyword Spotting at the Edge—0
WaveSense: Efficient Temporal Convolutions with Spiking Neural Networks for Keyword Spotting—0
Temporal Knowledge Distillation for On-device Audio Classification—0
SSAST: Self-Supervised Audio Spectrogram TransformerCode2
Attention-Free Keyword SpottingCode1
End-to-end Keyword Spotting using Xception-1dCode0
PEAF: Learnable Power Efficient Analog Acoustic Features for Audio Recognition—0
Multi-task Voice Activated Framework using Self-supervised Learning—0
Towards Robust Domain Generalization in 2D Neural Audio Processing—0
Speech-MLP: a simple MLP architecture for speech processing—0
A Lightweight dynamic filter for keyword spotting—0
Audiomer: A Convolutional Transformer For Keyword SpottingCode0
Behavior of Keyword Spotting Networks Under Noisy Conditions—0
Keyword spotting for audiovisual archival search in Uralic languages—0
Feature learning for efficient ASR-free keyword spotting in low-resource languages—0
Text Anchor Based Metric Learning for Small-footprint Keyword Spotting—0
Bifocal Neural ASR: Exploiting Keyword Spotting for Inference Optimization—0
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers—0
Multi-task Learning with Cross Attention for Keyword Spotting—0
AUC Optimization for Robust Small-footprint Keyword Spotting with Limited Training Data—0
An Integrated Framework for Two-pass Personalized Voice Trigger—0
PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation—0
Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis—0
Zero-Shot Federated Learning with New Classes for Audio Classification—0
MLPerf Tiny BenchmarkCode1
Broadcasted Residual Learning for Efficient Keyword SpottingCode1
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting—0
Teaching keyword spotters to spot new keywords with limited examples—0
Noisy student-teacher training for robust keyword spotting—0
A Streaming End-to-End Framework For Spoken Language Understanding—0
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 Quantization—0
The DKU System Description for The Interspeech 2021 Auto-KWS Challenge—0
A Probabilistic Framework for Lexicon-based Keyword Spotting in Handwritten Text Images—0
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 Classification—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