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 53015350 of 6433 papers

TitleStatusHype
Combining Multiple Views for Visual Speech Recognition0
Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword SpottingCode0
Embedding-Based Speaker Adaptive Training of Deep Neural Networks0
Convolutional Attention-based Seq2Seq Neural Network for End-to-End ASR0
Adapting general-purpose speech recognition engine output for domain-specific natural language question answering0
Contaminated speech training methods for robust DNN-HMM distant speech recognitionCode0
Keynote: Small Neural Nets Are Beautiful: Enabling Embedded Systems with Small Deep-Neural-Network Architectures0
Syntactic and Semantic Features For Code-Switching Factored Language Models0
Visual speech recognition: aligning terminologies for better understanding0
Which phoneme-to-viseme maps best improve visual-only computer lip-reading?0
Resolution limits on visual speech recognition0
Decoding visemes: improving machine lipreading0
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts0
Improving speech recognition by revising gated recurrent unitsCode0
Attention-based Wav2Text with Feature Transfer Learning0
Mitigating the Impact of Speech Recognition Errors on Chatbot using Sequence-to-Sequence Model0
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential DataCode0
Speech Recognition Challenge in the Wild: Arabic MGB-3Code0
WERd: Using Social Text Spelling Variants for Evaluating Dialectal Speech Recognition0
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges0
Language Modeling with Highway LSTM0
A Recorded Debating Dataset0
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification0
Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification0
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition SystemsCode0
End-to-End Audiovisual Fusion with LSTMs0
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks0
Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier0
Language Models of Spoken Dutch0
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic DataCode0
Gaussian Quadrature for Kernel Features0
Spoken English Intelligibility Remediation with PocketSphinx Alignment and Feature Extraction Improves Substantially over the State of the ArtCode0
Towards Quantum Language Models0
Word Transduction for Addressing the OOV Problem in Machine Translation for Similar Resource-Scarce Languages0
NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity0
Amharic-English Speech Translation in Tourism Domain0
Underspecification in Natural Language Understanding for Dialog Automation0
A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community0
Churn Identification in Microblogs using Convolutional Neural Networks with Structured Logical Knowledge0
A Text Normalisation System for Non-Standard English Words0
A deep-learning based native-language classification by using a latent semantic analysis for the NLI Shared Task 20170
Transliterated Mobile Keyboard Input via Weighted Finite-State Transducers0
Enriching ASR Lattices with POS Tags for Dependency Parsing0
Improving Machine Translation Quality Estimation with Neural Network Features0
Lexicon for Natural Language Generation in Spanish Adapted to Alternative and Augmentative Communication0
Multi-modal Summarization for Asynchronous Collection of Text, Image, Audio and Video0
The Microsoft Speech Language Translation (MSLT) Corpus for Chinese and Japanese: Conversational Test data for Machine Translation and Speech Recognition0
Byte-based Neural Machine Translation0
Speech- and Text-driven Features for Automated Scoring of English Speaking Tasks0
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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