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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 1876–1900 of 3012 papers

TitleStatusHype
Robustness of end-to-end Automatic Speech Recognition Models -- A Case Study using Mozilla DeepSpeech—0
Robustness of end-to-end Automatic Speech Recognition Models – A Case Study using Mozilla DeepSpeech—0
Robust Neural Machine Translation for Clean and Noisy Speech Transcripts—0
Robust Neural Machine Translation with ASR Errors—0
Robust Neural Machine Translation with Joint Textual and Phonetic Embedding—0
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems—0
Robust Prediction of Punctuation and Truecasing for Medical ASR—0
ROBUST SPEECH COMMAND RECOGNITION USING LABEL-DRIVEN TIME-FREQUENCY MASKING—0
Robust Spoken Language Understanding with RL-based Value Error Recovery—0
Robust Translation of French Live Speech Transcripts—0
Role of Intonation in Scoring Spoken English—0
Role of non-linear data processing on speech recognition task in the framework of reservoir computing—0
Role-specific Language Models for Processing Recorded Neuropsychological Exams—0
Romanization Encoding For Multilingual ASR—0
RSC: A Romanian Read Speech Corpus for Automatic Speech Recognition—0
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition—0
Run-and-back stitch search: novel block synchronous decoding for streaming encoder-decoder ASR—0
Run-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising—0
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus—0
SALM: Speech-augmented Language Model with In-context Learning for Speech Recognition and Translation—0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models—0
Samrómur Children: An Icelandic Speech Corpus—0
Samr\'omur: Crowd-sourcing Data Collection for Icelandic Speech Recognition—0
SAN: a robust end-to-end ASR model architecture—0
SapAugment: Learning A Sample Adaptive Policy for Data Augmentation—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