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 451500 of 6433 papers

TitleStatusHype
Efficient Sequence Transduction by Jointly Predicting Tokens and DurationsCode1
EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation LearningCode1
Attention-based Audio-Visual Fusion for Robust Automatic Speech RecognitionCode1
Emotionless: Privacy-Preserving Speech Analysis for Voice AssistantsCode1
Attention-based Contextual Language Model Adaptation for Speech RecognitionCode1
Empowering Whisper as a Joint Multi-Talker and Target-Talker Speech Recognition SystemCode1
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsCode1
Quilt-1M: One Million Image-Text Pairs for HistopathologyCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
Real-Time Multimodal Cognitive Assistant for Emergency Medical ServicesCode1
Attack on practical speaker verification system using universal adversarial perturbationsCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
A transfer learning based approach for pronunciation scoringCode1
End-to-End Speech Recognition from Federated Acoustic ModelsCode1
End-to-End Single-Channel Speaker-Turn Aware Conversational Speech TranslationCode1
End-to-End Speech Recognition and Disfluency RemovalCode1
Attention-Based Models for Speech RecognitionCode1
RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech RecognitionCode1
Enhancing Dysarthric Speech Recognition for Unseen Speakers via Prototype-Based AdaptationCode1
RNN Transducer Models For Spoken Language UnderstandingCode1
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language ModelsCode1
Romanian Speech Recognition Experiments from the ROBIN ProjectCode1
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data AugmentationCode1
ESB: A Benchmark For Multi-Domain End-to-End Speech RecognitionCode1
ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control CommunicationsCode1
Evaluating the visualization of what a Deep Neural Network has learnedCode1
Evaluating Speech Synthesis by Training Recognizers on Synthetic SpeechCode1
Deep Discriminative Feature Learning for Accent RecognitionCode1
How Much Context Does My Attention-Based ASR System Need?Code1
Self-Supervised Learning for speech recognition with Intermediate layer supervisionCode1
"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken ConversationsCode1
ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of KaldiCode1
How2: A Large-scale Dataset for Multimodal Language UnderstandingCode1
Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR ErrorsCode1
SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy MinimizationCode1
Shifted Chunk Encoder for Transformer Based Streaming End-to-End ASRCode1
Extending Whisper with prompt tuning to target-speaker ASRCode1
Fast Development of ASR in African Languages using Self Supervised Speech Representation LearningCode1
SLUE: New Benchmark Tasks for Spoken Language Understanding Evaluation on Natural SpeechCode1
Exploring Wav2vec 2.0 fine-tuning for improved speech emotion recognitionCode1
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
How Does Pre-trained Wav2Vec 2.0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control CommunicationsCode1
SoftCTC -- Semi-Supervised Learning for Text Recognition using Soft Pseudo-LabelsCode1
How to Teach DNNs to Pay Attention to the Visual Modality in Speech RecognitionCode1
HypR: A comprehensive study for ASR hypothesis revising with a reference corpusCode1
Fast-HuBERT: An Efficient Training Framework for Self-Supervised Speech Representation LearningCode1
FAST-RIR: Fast neural diffuse room impulse response generatorCode1
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API PredictionsCode1
FedScale: Benchmarking Model and System Performance of Federated Learning at ScaleCode1
A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and EnglishCode1
Show:102550
← PrevPage 10 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