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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 901–925 of 3012 papers

TitleStatusHype
Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation—0
Learning Speech Representation From Contrastive Token-Acoustic Pretraining—0
Contextual Biasing of Named-Entities with Large Language Models—0
Knowledge Distillation from Non-streaming to Streaming ASR Encoder using Auxiliary Non-streaming Layer—0
ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers—0
Unsupervised Active Learning: Optimizing Labeling Cost-Effectiveness for Automatic Speech Recognition—0
Decoupled Structure for Improved Adaptability of End-to-End Models—0
A Small and Fast BERT for Chinese Medical Punctuation RestorationCode0
Convoifilter: A case study of doing cocktail party speech recognition—0
TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition—0
Indonesian Automatic Speech Recognition with XLSR-53—0
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction—0
Radio2Text: Streaming Speech Recognition Using mmWave Radio Signals—0
Accurate synthesis of Dysarthric Speech for ASR data augmentation—0
End-to-End Open Vocabulary Keyword Search With Multilingual Neural RepresentationsCode0
Improving CTC-AED model with integrated-CTC and auxiliary loss regularization—0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
Using Text Injection to Improve Recognition of Personal Identifiers in Speech—0
Text Injection for Capitalization and Turn-Taking Prediction in Speech Models—0
Bilingual Streaming ASR with Grapheme units and Auxiliary Monolingual Loss—0
A Novel Self-training Approach for Low-resource Speech Recognition—0
Comparative Analysis of the wav2vec 2.0 Feature Extractor—0
Boosting Chinese ASR Error Correction with Dynamic Error Scaling Mechanism—0
ApproBiVT: Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff Guided Early Stopping and Checkpoint Averaging—0
Cascaded Cross-Modal Transformer for Request and Complaint Detection—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