SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 58515900 of 6433 papers

TitleStatusHype
Data Selection With Fewer Words0
Turn-taking phenomena in incremental dialogue systems0
Dialogue Management based on Multi-domain Corpus0
Open-Domain Name Error Detection using a Multi-Task RNN0
Keynote: Graph-based Approaches for Spoken Language Understanding0
Predicting disordered speech comprehensibility from Goodness of Pronunciation scores0
User Adaptive Restoration for Incorrectly-Segmented Utterances in Spoken Dialogue Systems0
Determining an Optimal Set of Flesh Points on Tongue, Lips, and Jaw for Continuous Silent Speech Recognition0
Analysis of Dysarthric Speech using Distinctive Feature Recognition0
Arabic Diacritization with Recurrent Neural Networks0
Automatic dysfluency detection in dysarthric speech using deep belief networks0
Improved Arabic Dialect Classification with Social Media Data0
Pre-Computable Multi-Layer Neural Network Language Models0
A Coarse-Grained Model for Optimal Coupling of ASR and SMT Systems for Speech Translation0
A distributed cloud-based dialog system for conversational application development0
Improving Arabic Diacritization through Syntactic Analysis0
Model adaptation and adaptive training for the recognition of dysarthric speech0
A Discriminative Training Procedure for Continuous Translation Models0
The Cohort and Speechify Libraries for Rapid Construction of Speech Enabled Applications for Android0
Recognition of Distress Calls in Distant Speech Setting: a Preliminary Experiment in a Smart Home0
Learning Domain-Independent Dialogue Policies via Ontology Parameterisation0
Learning a Deep Hybrid Model for Semi-Supervised Text Classification0
Recurrent Polynomial Network for Dialogue State Tracking with Mismatched Semantic Parsers0
Recognizing Dysarthric Speech due to Amyotrophic Lateral Sclerosis with Across-Speaker Articulatory Normalization0
Personalized Machine Translation: Predicting Translational Preferences0
SHEF-NN: Translation Quality Estimation with Neural Networks0
Large Linguistic Corpus Reduction with SCP Algorithms0
Partitioning Large Scale Deep Belief Networks Using Dropout0
End-to-End Attention-based Large Vocabulary Speech RecognitionCode0
Probabilistic Modelling of Morphologically Rich Languages0
An End-to-End Neural Network for Polyphonic Piano Music TranscriptionCode0
EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based DecodingCode0
Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition0
Neural NILM: Deep Neural Networks Applied to Energy DisaggregationCode0
Robust speech recognition using consensus function based on multi-layer networks0
Discriminative Segmental Cascades for Feature-Rich Phone Recognition0
Feature Normalisation for Robust Speech Recognition0
Incremental LSTM-based Dialog State Tracker0
Describing Multimedia Content using Attention-based Encoder--Decoder Networks0
Trans-dimensional Random Fields for Language Modeling0
Best Practices for Crowdsourcing Dialectal Arabic Speech Transcription0
Semantic Role Labeling Improves Incremental Parsing0
Revisiting Word Embedding for Contrasting MeaningCode0
Counting What Counts: Decompounding for Keyphrase Extraction0
Multi-Reference Evaluation for Dialectal Speech Recognition System: A Study for Egyptian ASR0
NCSU\_SAS\_WOOKHEE: A Deep Contextual Long-Short Term Memory Model for Text Normalization0
Sentence selection for automatic scoring of Mandarin proficiency0
The Fixed-Size Ordinally-Forgetting Encoding Method for Neural Network Language Models0
Efficient Disfluency Detection with Transition-based Parsing0
Driving ROVER with Segment-based ASR Quality Estimation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified