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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 2726–2750 of 3012 papers

TitleStatusHype
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding—0
ASR in German: A Detailed Error Analysis—0
ASR is all you need: cross-modal distillation for lip reading—0
ASR Rescoring and Confidence Estimation with ELECTRA—0
Assessing ASR Model Quality on Disordered Speech using BERTScore—0
Assessing the Performance of Automatic Speech Recognition Systems When Used by Native and Non-Native Speakers of Three Major Languages in Dictation Workflows—0
Assessing the Tolerance of Neural Machine Translation Systems Against Speech Recognition Errors—0
ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers—0
ASTRA: Aligning Speech and Text Representations for Asr without Sampling—0
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech—0
A Study of All-Convolutional Encoders for Connectionist Temporal Classification—0
A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems—0
A Study of Non-autoregressive Model for Sequence Generation—0
A Study on Lip Localization Techniques used for Lip reading from a Video—0
A study on native American English speech recognition by Indian listeners with varying word familiarity level—0
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge—0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding—0
A study on the impact of Self-Supervised Learning on automatic dysarthric speech assessment—0
A Subband-Based SVM Front-End for Robust ASR—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
A Survey on Speech Large Language Models—0
Asynchronous Decentralized Distributed Training of Acoustic Models—0
ATC-ANNO: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation—0
ATCSpeech: a multilingual pilot-controller speech corpus from real Air Traffic Control environment—0
ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systems—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