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 301–350 of 407 papers

TitleStatusHype
Learning To Detect Keyword Parts And Whole By Smoothed Max Pooling—0
Performance-Oriented Neural Architecture Search—0
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection—0
Predicting detection filters for small footprint open-vocabulary keyword spotting—0
Small-footprint Keyword Spotting with Graph Convolutional Network—0
Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-ConvolutionsCode0
Honkling: In-Browser Personalization for Ubiquitous Keyword SpottingCode0
Temporal Feedback Convolutional Recurrent Neural Networks for Speech Command RecognitionCode0
Adversarial Example Detection by Classification for Deep Speech RecognitionCode0
Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wildCode0
Query-by-example on-device keyword spotting—0
Orthogonality Constrained Multi-Head Attention For Keyword Spotting—0
Spoken Language Identification using ConvNets—0
Keyword Spotter Model for Crop Pest and Disease Monitoring from Community Radio Data—0
A Channel-Pruned and Weight-Binarized Convolutional Neural Network for Keyword Spotting—0
Multi-layer Attention Mechanism for Speech Keyword Recognition—0
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation—0
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training—0
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers—0
A Monaural Speech Enhancement Method for Robust Small-Footprint Keyword Spotting—0
An Alternative Deep Feature Approach to Line Level Keyword Spotting—0
SpeechYOLO: Detection and Localization of Speech Objects—0
Temporal Convolution for Real-time Keyword Spotting on Mobile DevicesCode0
On evaluating CNN representations for low resource medical image classification—0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications—0
An Optimized Recurrent Unit for Ultra-Low-Power Keyword Spotting—0
An In-Vehicle KWS System with Multi-Source Fusion for Vehicle Applications—0
Effective Combination of DenseNet andBiLSTM for Keyword Spotting—0
Bonseyes AI Pipeline -- bringing AI to you. End-to-end integration of data, algorithms and deployment tools—0
Prototypical Metric Transfer Learning for Continuous Speech Keyword Spotting With Limited Training Data—0
An Investigation of Few-Shot Learning in Spoken Term ClassificationCode0
Streaming Voice Query Recognition using Causal Convolutional Recurrent Neural Networks—0
End-to-End Streaming Keyword Spotting—0
Benchmarking Keyword Spotting Efficiency on Neuromorphic HardwareCode0
DONUT: CTC-based Query-by-Example Keyword SpottingCode0
Efficient keyword spotting using dilated convolutions and gatingCode0
Stochastic Adaptive Neural Architecture Search for Keyword SpottingCode0
Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders—0
Hierarchical Neural Network Architecture In Keyword Spotting—0
JavaScript Convolutional Neural Networks for Keyword Spotting in the Browser: An Experimental AnalysisCode0
DONUT: CTC-based Query-by-Example Keyword Spotting—0
Robust Spoken Term Detection Automatically Adjusted for a Given Threshold—0
Low-bit quantization and quantization-aware training for small-footprint keyword spotting—0
Federated Learning for Keyword SpottingCode0
Efficient keyword spotting using time delay neural networks—0
Sequence Discriminative Training for Deep Learning based Acoustic Keyword Spotting—0
Transfer Learning for a Letter-Ngrams to Word Decoder in the Context of Historical Handwriting Recognition with Scarce Resources—0
Data Augmentation for Robust Keyword Spotting under Playback Interference—0
Automatic Speech Recognition for Humanitarian Applications in Somali—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