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 34513500 of 6433 papers

TitleStatusHype
Residual Energy-Based Models for End-to-End Speech Recognition0
Real-time low-resource phoneme recognition on edge devicesCode0
An Approach to Improve Robustness of NLP Systems against ASR Errors0
Voice Privacy with Smart Digital Assistants in Educational Settings0
Evolving Learning Rate Optimizers for Deep Neural Networks0
Hallucination of speech recognition errors with sequence to sequence learning0
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition SystemsCode0
Contextual Biasing of Language Models for Speech Recognition in Goal-Oriented Conversational Agents0
Advancing RNN Transducer Technology for Speech Recognition0
Transformer-based ASR Incorporating Time-reduction Layer and Fine-tuning with Self-Knowledge Distillation0
Distributed Deep Learning Using Volunteer Computing-Like Paradigm0
Fast Development of ASR in African Languages using Self Supervised Speech Representation LearningCode1
XLST: Cross-lingual Self-training to Learn Multilingual Representation for Low Resource Speech Recognition0
Towards the evaluation of automatic simultaneous speech translation from a communicative perspective0
EdgeCRNN: an edgecomputing oriented model of acoustic feature enhancement for keyword spotting0
OkwuGbé: End-to-End Speech Recognition for Fon and IgboCode0
A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training0
Uncertainty-guided Model Generalization to Unseen Domains0
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition0
Learning Word-Level Confidence For Subword End-to-End ASR0
Best of Both Worlds: Robust Accented Speech Recognition with Adversarial Transfer Learning0
Fine-tuning of Pre-trained End-to-end Speech Recognition with Generative Adversarial Networks0
Contrastive Semi-supervised Learning for ASR0
An Ultra-low Power RNN Classifier for Always-On Voice Wake-Up Detection Robust to Real-World Scenarios0
A Parallelizable Lattice Rescoring Strategy with Neural Language ModelsCode3
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research ChallengesCode1
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration0
WaveGuard: Understanding and Mitigating Audio Adversarial ExamplesCode1
The Spatial Selective Auditory Attention of Cochlear Implant Users in Different Conversational Sound Levels0
Continuous Speech Separation with Ad Hoc Microphone Arrays0
Domain Generalization: A Survey0
Incorporating VAD into ASR System by Multi-task Learning0
Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event LocalizationCode0
Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition0
Silent versus modal multi-speaker speech recognition from ultrasound and video0
Meta-Learning for improving rare word recognition in end-to-end ASR0
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition0
Speech Enhancement Using Multi-Stage Self-Attentive Temporal Convolutional Networks0
SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter0
Thoughts on the potential to compensate a hearing loss in noise0
End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend0
Unidirectional Memory-Self-Attention Transducer for Online Speech Recognition0
Senone-aware Adversarial Multi-task Training for Unsupervised Child to Adult Speech Adaptation0
Evolutionary optimization of contexts for phonetic correction in speech recognition systems0
Memory-efficient Speech Recognition on Smart Devices0
Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial DomainCode0
Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model0
The Use of Voice Source Features for Sung Speech Recognition0
End-to-End Neural Systems for Automatic Children Speech Recognition: An Empirical Study0
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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