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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 151–175 of 3012 papers

TitleStatusHype
Attention-based Contextual Language Model Adaptation for Speech RecognitionCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
A context-aware knowledge transferring strategy for CTC-based ASRCode1
Attentive Sequence-to-Sequence Learning for Diacritic Restoration of Yorùbá Language TextCode1
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applicationsCode1
Audio-Visual Efficient Conformer for Robust Speech RecognitionCode1
Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation ModelsCode1
Evolutionary Prompt Design for LLM-Based Post-ASR Error CorrectionCode1
Attention-based Audio-Visual Fusion for Robust Automatic Speech RecognitionCode1
ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversionCode1
Automatic Speech Recognition Benchmark for Air-Traffic CommunicationsCode1
Automatic Speech Recognition for Speech Assessment of Persian Preschool ChildrenCode1
Accented Speech Recognition With Accent-specific CodebooksCode1
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling InsightsCode1
AVATAR: Unconstrained Audiovisual Speech RecognitionCode1
AVLnet: Learning Audio-Visual Language Representations from Instructional VideosCode1
BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control CommunicationsCode1
Automatic Disfluency Detection from Untranscribed SpeechCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech RecognitionCode1
End-to-End Speech Recognition from Federated Acoustic ModelsCode1
Google Crowdsourced Speech Corpora and Related Open-Source Resources for Low-Resource Languages and Dialects: An OverviewCode1
Gradient Remedy for Multi-Task Learning in End-to-End Noise-Robust Speech RecognitionCode1
Fast Development of ASR in African Languages using Self Supervised Speech Representation LearningCode1
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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