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 23012350 of 6433 papers

TitleStatusHype
UserLibri: A Dataset for ASR Personalization Using Only Text0
Improving Transformer-based Conversational ASR by Inter-Sentential Attention Mechanism0
Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition0
Exploring the Effect of Dialect Mismatched Language Models in Telugu Automatic Speech Recognition0
FPI: Failure Point Isolation in Large-scale Conversational Assistants0
BehancePR: A Punctuation Restoration Dataset for Livestreaming Video TranscriptCode0
Domain-Informed Probing of wav2vec 2.0 Embeddings for Phonetic Features0
Non-Autoregressive Chinese ASR Error Correction with Phonological Training0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms0
On Assessing and Developing Spoken ’Grammatical Error Correction’ Systems0
Improving Low-Resource Speech Recognition with Pretrained Speech Models: Continued Pretraining vs. Semi-Supervised Training0
Updating Only Encoders Prevents Catastrophic Forgetting of End-to-End ASR Models0
FeaRLESS: Feature Refinement Loss for Ensembling Self-Supervised Learning Features in Robust End-to-end Speech Recognition0
Sub-8-Bit Quantization Aware Training for 8-Bit Neural Network Accelerator with On-Device Speech Recognition0
STOP: A dataset for Spoken Task Oriented Semantic Parsing0
Space-Efficient Representation of Entity-centric Query Language Models0
The THUEE System Description for the IARPA OpenASR21 Challenge0
Nextformer: A ConvNeXt Augmented Conformer For End-To-End Speech RecognitionCode1
Language-specific Characteristic Assistance for Code-switching Speech Recognition0
Exploring linguistic feature and model combination for speech recognition based automatic AD detection0
Bengali Common Voice Speech Dataset for Automatic Speech Recognition0
Challenges and Opportunities in Multi-device Speech Processing0
TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline0
Meta Auxiliary Learning for Low-resource Spoken Language Understanding0
Improving the Training Recipe for a Robust Conformer-based Hybrid Model0
On Comparison of Encoders for Attention based End to End Speech Recognition in Standalone and Rescoring Mode0
Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspective0
Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi0
Distilling a Pretrained Language Model to a Multilingual ASR ModelCode1
TEVR: Improving Speech Recognition by Token Entropy Variance ReductionCode2
Confidence Score Based Conformer Speaker Adaptation for Speech Recognition0
PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis0
Pruned RNN-T for fast, memory-efficient ASR training0
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection0
Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systems0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data0
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
Answer Fast: Accelerating BERT on the Tensor Streaming Processor0
Supervision-Guided Codebooks for Masked Prediction in Speech Pre-training0
The Makerere Radio Speech Corpus: A Luganda Radio Corpus for Automatic Speech Recognition0
Boosting Cross-Domain Speech Recognition with Self-SupervisionCode0
Transfer Learning for Robust Low-Resource Children's Speech ASR with Transformers and Source-Filter Warping0
0/1 Deep Neural Networks via Block Coordinate Descent0
Decoupled Federated Learning for ASR with Non-IID Data0
Developing a Speech Recognition System for Recognizing Tonal Speech Signals Using a Convolutional Neural Network0
DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR0
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition0
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition0
SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic LearningCode2
AVATAR: Unconstrained Audiovisual Speech RecognitionCode1
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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