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 60516100 of 6433 papers

TitleStatusHype
Discovering Latent Structure in Task-Oriented Dialogues0
Aided diagnosis of dementia type through computer-based analysis of spontaneous speech0
Using Ellipsis Detection and Word Similarity for Transformation of Spoken Language into Grammatically Valid Sentences0
Word-Based Dialog State Tracking with Recurrent Neural Networks0
InproTKs: A Toolkit for Incremental Situated Processing0
Sliding Alignment Windows for Real-Time Crowd Captioning0
Automatic evaluation of spoken summaries: the case of language assessment0
Towards End-To-End Speech Recognition with Recurrent Neural Networks0
Dive deeper: Deep Semantics for Sentiment Analysis0
Word Segmentation of Informal Arabic with Domain Adaptation0
SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue0
Dropout: A Simple Way to Prevent Neural Networks from Overfitting0
Fast and Robust Neural Network Joint Models for Statistical Machine Translation0
Unsupervised Adaptation for Statistical Machine Translation0
Sequential Labeling for Tracking Dynamic Dialog States0
Rate-Invariant Analysis of Trajectories on Riemannian Manifolds with Application in Visual Speech Recognition0
Design and Optimization of a Speech Recognition Front-End for Distant-Talking Control of a Music Playback Device0
A Corpus and Phonetic Dictionary for Tunisian Arabic Speech Recognition0
Mapping Diatopic and Diachronic Variation in Spoken Czech: The ORTOFON and DIALEKT Corpora0
Euronews: a multilingual speech corpus for ASR0
Turkish Resources for Visual Word Recognition0
TUKE-BNews-SK: Slovak Broadcast News Corpus Construction and Evaluation0
A LDA-Based Topic Classification Approach From Highly Imperfect Automatic Transcriptions0
Enhancing the TED-LIUM Corpus with Selected Data for Language Modeling and More TED Talks0
Comparison of Gender- and Speaker-adaptive Emotion Recognition0
A Multimodal Corpus of Rapid Dialogue Games0
SAVAS: Collecting, Annotating and Sharing Audiovisual Language Resources for Automatic Subtitling0
Computer-Aided Quality Assurance of an Icelandic Pronunciation Dictionary0
Exploiting the large-scale German Broadcast Corpus to boost the Fraunhofer IAIS Speech Recognition System0
Speech Recognition Web Services for Dutch0
Morpho-Syntactic Study of Errors from Speech Recognition System0
Semi-automatic annotation of the UCU accents speech corpus0
El-WOZ: a client-server wizard-of-oz interface0
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather0
Multimodal Corpora for Silent Speech Interaction0
A New Form of Humor --- Mapping Constraint-Based Computational Morphologies to a Finite-State Representation0
Revising the annotation of a Broadcast News corpus: a linguistic approach0
Student achievement and French sentence repetition test scores0
Towards Multilingual Conversations in the Medical Domain: Development of Multilingual Medical Data and A Network-based ASR System0
New functions for a multipurpose multimodal tool for phonetic and linguistic analysis of very large speech corpora0
N-gram Counts and Language Models from the Common Crawl0
Using a Serious Game to Collect a Child Learner Speech Corpus0
DINASTI: Dialogues with a Negotiating Appointment Setting Interface0
Rediscovering 15 Years of Discoveries in Language Resources and Evaluation: The LREC Anthology Analysis0
On the use of a fuzzy classifier to speed up the Sp\_ToBI labeling of the Glissando Spanish corpus0
Development of a TV Broadcasts Speech Recognition System for Qatari Arabic0
Utilizing constituent structure for compound analysis0
Basque Speecon-like and Basque SpeechDat MDB-600: speech databases for the development of ASR technology for Basque0
The WaveSurfer Automatic Speech Recognition Plugin0
Human annotation of ASR error regions: Is ``gravity'' a sharable concept for human annotators?0
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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