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 2211–2220 of 3012 papers

Title	Date	Tasks	Status
Dynamic Masking for Improved Stability in Spoken Language Translation	May 30, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling	May 25, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
FT Speech: Danish Parliament Speech Corpus	May 25, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
An Audio-enriched BERT-based Framework for Spoken Multiple-choice Question Answering	May 25, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification	May 24, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available
Large scale evaluation of importance maps in automatic speech recognition	May 21, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Investigation of Large-Margin Softmax in Neural Language Modeling	May 20, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Early Stage LM Integration Using Local and Global Log-Linear Combination	May 20, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Comparison of Label-Synchronous and Frame-Synchronous End-to-End Models for Speech Recognition	May 20, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Improving Proper Noun Recognition in End-to-End ASR By Customization of the MWER Loss Criterion	May 19, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified

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All datasets LRS2 RealMAN Sagalee HUI speech corpus LRS3-TED M-AILabs speech dataset The Spoken Wikipedia Corpora Voxforge German VoxPopuli

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TM-CTC	Test WER	10.1	—	Unverified
2	TM-seq2seq	Test WER	9.7	—	Unverified
3	CTC/attention	Test WER	8.2	—	Unverified
4	LF-MMI TDNN	Test WER	6.7	—	Unverified
5	Whisper-LLaMA	Test WER	6.6	—	Unverified
6	End2end Conformer	Test WER	3.9	—	Unverified
7	End2end Conformer	Test WER	3.7	—	Unverified
8	MoCo + wav2vec (w/o extLM)	Test WER	2.7	—	Unverified
9	CTC/Attention	Test WER	1.5	—	Unverified
10	Whisper	Test WER	1.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SpatialNet	CER	14.5	—	Unverified
2	CleanMel-L-mask	CER	14.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer	Test WER	15.32	—	Unverified
2	Whisper-largev3-finetuned	Test WER	10.82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer Transducer	WER (%)	1.89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DistillAV	WER	1.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer Transducer	WER (%)	4.28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer Transducer	WER (%)	8.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer Transducer	WER (%)	3.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Conformer Transducer (German)	WER (%)	8.98	—	Unverified