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 36013650 of 6433 papers

TitleStatusHype
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yol\'oxochitl Mixtec0
Dialect Identification through Adversarial Learning and Knowledge Distillation on Romanian BERT0
Tutorial Proposal: End-to-End Speech Translation0
Context-sensitive evaluation of automatic speech recognition: considering user experience & language variation0
Configurable Privacy-Preserving Automatic Speech Recognition0
A Survey on Paralinguistics in Tamil Speech Processing0
Interactive spatial speech recognition maps based on simulated speech recognition experiments0
XY Neural Networks0
Compressing 1D Time-Channel Separable Convolutions using Sparse Random Ternary Matrices0
Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone0
Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition0
Adversarial Attacks and Defenses for Speech Recognition Systems0
A study of latent monotonic attention variants0
Multiple-hypothesis CTC-based semi-supervised adaptation of end-to-end speech recognition0
Transformer-based end-to-end speech recognition with residual Gaussian-based self-attention0
Scaling sparsemax based channel selection for speech recognition with ad-hoc microphone arrays0
Improved Meta-Learning Training for Speaker Verification0
Shrinking Bigfoot: Reducing wav2vec 2.0 footprint0
Quantifying Bias in Automatic Speech RecognitionCode0
BART based semantic correction for Mandarin automatic speech recognition system0
Construction of a Large-scale Japanese ASR Corpus on TV Recordings0
Mutually-Constrained Monotonic Multihead Attention for Online ASR0
An Approach to Improve Robustness of NLP Systems against ASR Errors0
Real-time low-resource phoneme recognition on edge devicesCode0
Residual Energy-Based Models for End-to-End Speech Recognition0
Voice Privacy with Smart Digital Assistants in Educational Settings0
Hallucination of speech recognition errors with sequence to sequence learning0
Evolving Learning Rate Optimizers for Deep Neural Networks0
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
Transformer-based ASR Incorporating Time-reduction Layer and Fine-tuning with Self-Knowledge Distillation0
Advancing RNN Transducer Technology for Speech Recognition0
Distributed Deep Learning Using Volunteer Computing-Like Paradigm0
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
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition0
A Distributed Optimisation Framework Combining Natural Gradient with Hessian-Free for Discriminative Sequence Training0
Uncertainty-guided Model Generalization to Unseen Domains0
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
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration0
Domain Generalization: A Survey0
Continuous Speech Separation with Ad Hoc Microphone Arrays0
The Spatial Selective Auditory Attention of Cochlear Implant Users in Different Conversational Sound Levels0
Incorporating VAD into ASR System by Multi-task Learning0
Show:102550
← PrevPage 73 of 129Next →

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