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 1821–1830 of 3012 papers

Title	Date	Tasks	Status
Unsupervised Stemming based Language Model for Telugu Broadcast News Transcription	Aug 10, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Unveiling Biases while Embracing Sustainability: Assessing the Dual Challenges of Automatic Speech Recognition Systems	Mar 2, 2025	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Updating Only Encoders Prevents Catastrophic Forgetting of End-to-End ASR Models	Jul 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Useful Blunders: Can Automated Speech Recognition Errors Improve Downstream Dementia Classification?	Jan 10, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Use of Knowledge Graph in Rescoring the N-Best List in Automatic Speech Recognition	May 22, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis	Dec 15, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using Ambiguity Detection to Streamline Linguistic Annotation	Dec 1, 2016	Automatic Speech Recognition (ASR)Machine Translation	—Unverified
Using Automatic Speech Recognition in Spoken Corpus Curation	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using English Acoustic Models for Hindi Automatic Speech Recognition	Dec 1, 2012	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition	Jun 14, 2021	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