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Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

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Showing 1326–1350 of 3012 papers

TitleStatusHype
End-to-end speech recognition modeling from de-identified data—0
pMCT: Patched Multi-Condition Training for Robust Speech Recognition—0
Online Continual Learning of End-to-End Speech Recognition Models—0
Speaker Anonymization with Phonetic Intermediate Representations—0
Investigating the Impact of Cross-lingual Acoustic-Phonetic Similarities on Multilingual Speech Recognition—0
End-to-end Speech-to-Punctuated-Text Recognition—0
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies—0
Compute Cost Amortized Transformer for Streaming ASR—0
Vietnamese Capitalization and Punctuation Recovery ModelsCode0
Leveraging Acoustic Contextual Representation by Audio-textual Cross-modal Learning for Conversational ASR—0
Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition—0
Improving Transformer-based Conversational ASR by Inter-Sentential Attention Mechanism—0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms—0
Improving Low-Resource Speech Recognition with Pretrained Speech Models: Continued Pretraining vs. Semi-Supervised Training—0
Updating Only Encoders Prevents Catastrophic Forgetting of End-to-End ASR Models—0
Non-Autoregressive Chinese ASR Error Correction with Phonological Training—0
Exploring the Effect of Dialect Mismatched Language Models in Telugu Automatic Speech Recognition—0
BehancePR: A Punctuation Restoration Dataset for Livestreaming Video TranscriptCode0
FeaRLESS: Feature Refinement Loss for Ensembling Self-Supervised Learning Features in Robust End-to-end Speech Recognition—0
Space-Efficient Representation of Entity-centric Query Language Models—0
The THUEE System Description for the IARPA OpenASR21 Challenge—0
STOP: A dataset for Spoken Task Oriented Semantic Parsing—0
Bengali Common Voice Speech Dataset for Automatic Speech Recognition—0
TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline—0
Challenges and Opportunities in Multi-device Speech Processing—0
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All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1—Unverified
2TM-seq2seqTest WER9.7—Unverified
3CTC/attentionTest WER8.2—Unverified
4LF-MMI TDNNTest WER6.7—Unverified
5Whisper-LLaMATest WER6.6—Unverified
6End2end ConformerTest WER3.9—Unverified
7End2end ConformerTest WER3.7—Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7—Unverified
9CTC/AttentionTest WER1.5—Unverified
10WhisperTest WER1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5—Unverified
2CleanMel-L-maskCER14.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32—Unverified
2Whisper-largev3-finetunedTest WER10.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89—Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98—Unverified