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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 1951–1975 of 3012 papers

TitleStatusHype
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition—0
Multi-channel Multi-frame ADL-MVDR for Target Speech Separation—0
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews—0
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition—0
Adjust-free adversarial example generation in speech recognition using evolutionary multi-objective optimization under black-box condition—0
Toward Streaming ASR with Non-Autoregressive Insertion-based Model—0
User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis—0
Exploring Transfer Learning For End-to-End Spoken Language Understanding—0
A review of on-device fully neural end-to-end automatic speech recognition algorithms—0
AV Taris: Online Audio-Visual Speech RecognitionCode1
Less Is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging—0
Improved Robustness to Disfluencies in RNN-Transducer Based Speech Recognition—0
On Knowledge Distillation for Direct Speech Translation—0
Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition—0
Using multiple ASR hypotheses to boost i18n NLU performance—0
MLS: A Large-Scale Multilingual Dataset for Speech ResearchCode0
End to End ASR System with Automatic Punctuation InsertionCode0
ASR for Non-standardised Languages with Dialectal Variation: the case of Swiss German—0
Sparse Transcription—0
German-Arabic Speech-to-Speech Translation for Psychiatric Diagnosis—0
End-to-End Automatic Speech Recognition for GujaratiCode1
On-Device detection of sentence completion for voice assistants with low-memory footprint—0
100,000 Podcasts: A Spoken English Document Corpus—0
The Indigenous Languages Technology project at NRC Canada: An empowerment-oriented approach to developing language software—0
A Comprehensive Evaluation of Incremental Speech Recognition and Diarization for Conversational AICode0
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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