SOTAVerified

Keyword Spotting

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

( Image credit: Simon Grest )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 407 papers

TitleStatusHype
ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages—0
Weight-importance sparse training in keyword spotting—0
Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring—0
Visually grounded cross-lingual keyword spotting in speech—0
Resource-Efficient Neural Architect—0
A Bird's-eye View of Language Processing Projects at the Romanian Academy—0
Developing Far-Field Speaker System Via Teacher-Student Learning—0
Attention-based End-to-End Models for Small-Footprint Keyword SpottingCode0
Speech Recognition: Keyword Spotting Through Image Recognition—0
Zone-based Keyword Spotting in Bangla and Devanagari Documents—0
Multiple-Instance, Cascaded Classification for Keyword Spotting in Narrow-Band Audio—0
Hello Edge: Keyword Spotting on MicrocontrollersCode0
Streaming Small-Footprint Keyword Spotting using Sequence-to-Sequence Models—0
Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword SpottingCode0
Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier—0
Word Searching in Scene Image and Video Frame in Multi-Script Scenario using Dynamic Shape Coding—0
Polish Read Speech Corpus for Speech Tools and Services—0
READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival DocumentsCode0
Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting—0
Automatic Extraction of News Values from Headline Text—0
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting—0
Characterizing Linguistic Attributes for Automatic Classification of Intent Based Racist/Radicalized Posts on Tumblr Micro-Blogging Website—0
Neural Morphological Analysis: Encoding-Decoding Canonical Segments—0
The Effects of Data Collection Methods in Twitter—0
Trainable Frontend For Robust and Far-Field Keyword SpottingCode0
A Joint Model of Orthography and Morphological Segmentation—0
Online Keyword Spotting with a Character-Level Recurrent Neural Network—0
Structured Transforms for Small-Footprint Deep Learning—0
CUNY Systems for the Query-by-Example Search on Speech Task at MediaEval 2015—0
The SPL-IT-UC Query by Example Search on Speech system for MediaEval 2015—0
ELiRF at MediaEval 2015: Query by Example Search on Speech Task (QUESST)—0
The NNI Query-by-Example System for MediaEval 2015—0
NTU System at MediaEval 2015: Zero Resource Query by Example Spoken Term Detection Using Deep and Recurrent Neural Networks—0
The IIT-B Query-by-Example System for MediaEval 2015—0
TUKE at MediaEval 2015 QUESST—0
GTM-UVigo Systems for the Query-by-Example Search on Speech Task at MediaEval 2015Code0
BUT QUESST 2015 System Description—0
Speech and language technologies for the automatic monitoring and training of cognitive functions—0
Finding Opinion Manipulation Trolls in News Community Forums—0
What’s Cookin’? Interpreting Cooking Videos using Text, Speech and VisionCode0
What's Cookin'? Interpreting Cooking Videos using Text, Speech and VisionCode0
The NNI Query-by-Example System for MediaEval 2014—0
IIIT-H System for MediaEval 2014 QUESST—0
BUT QUESST 2014 System Description—0
ELiRF at MediaEval 2014: Query by Example Search on Speech Task (QUESST)—0
The SPL-IT Query by Example Search on Speech system for MediaEval 2014—0
GTTS-EHU Systems for QUESST at MediaEval 2014—0
TUKE System for MediaEval 2014 QUESST—0
CUHK System for QUESST Task of MediaEval 2014—0
Morphological Segmentation for Keyword Spotting—0
Show:102550
← PrevPage 8 of 9Next →
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