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 151–200 of 407 papers

TitleStatusHype
Improving vision-inspired keyword spotting using dynamic module skipping in streaming conformer encoder—0
Improving Small Footprint Few-shot Keyword Spotting with Supervision on Auxiliary Data—0
Flexible Keyword Spotting based on Homogeneous Audio-Text Embedding—0
Keyword Spotting Simplified: A Segmentation-Free Approach using Character Counting and CTC re-scoringCode0
Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal StatisticsCode0
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition—0
On-Device Constrained Self-Supervised Speech Representation Learning for Keyword Spotting via Knowledge Distillation—0
Matching Latent Encoding for Audio-Text based Keyword Spotting—0
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili—0
Spot keywords from very noisy and mixed speech—0
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting—0
Conditional Online Learning for Keyword Spotting—0
TACos: Learning Temporally Structured Embeddings for Few-Shot Keyword Spotting with Dynamic Time WarpingCode0
Semi-Supervised Federated Learning for Keyword SpottingCode0
An Exploration into the Performance of Unsupervised Cross-Task Speech Representations for "In the Wild'' Edge Applications—0
Plug-and-Play Multilingual Few-shot Spoken Words Recognition—0
Small-footprint slimmable networks for keyword spotting—0
Multilingual Query-by-Example Keyword Spotting with Metric Learning and Phoneme-to-Embedding Mapping—0
How Tiny Can Analog Filterbank Features Be Made for Ultra-low-power On-device Keyword Spotting?—0
Unsupervised Speech Representation Pooling Using Vector QuantizationCode0
To Wake-up or Not to Wake-up: Reducing Keyword False Alarm by Successive Refinement—0
AraSpot: Arabic Spoken Command SpottingCode0
Exploring Representation Learning for Small-Footprint Keyword Spotting—0
Self-supervised speech representation learning for keyword-spotting with light-weight transformers—0
ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents—0
Fixed-point quantization aware training for on-device keyword-spotting—0
Scalable Weight Reparametrization for Efficient Transfer Learning—0
Locale Encoding For Scalable Multilingual Keyword Spotting Models—0
Speech Privacy Leakage from Shared Gradients in Distributed Learning—0
A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons—0
Analyzing the Representational Geometry of Acoustic Word Embeddings—0
VSVC: Backdoor attack against Keyword Spotting based on Voiceprint Selection and Voice Conversion—0
Learnable Front Ends Based on Temporal Modulation for Music Tagging—0
Filterbank Learning for Noise-Robust Small-Footprint Keyword Spotting—0
PBSM: Backdoor attack against Keyword spotting based on pitch boosting and sound masking—0
Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting—0
LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting—0
Integrated Parameter-Efficient Tuning for General-Purpose Audio ModelsCode0
Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach—0
Metric Learning for User-defined Keyword Spotting—0
Application of Knowledge Distillation to Multi-task Speech Representation Learning—0
Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the InputCode0
HEiMDaL: Highly Efficient Method for Detection and Localization of wake-words—0
Discriminatory and orthogonal feature learning for noise robust keyword spotting—0
Fully Unsupervised Training of Few-shot Keyword Spotting—0
Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase—0
Recycle Your Wav2Vec2 Codebook: A Speech Perceiver for Keyword Spotting—0
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts—0
ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales—0
An Anchor-Free Detector for Continuous Speech Keyword Spotting—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