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 1831–1840 of 3012 papers

Title	Date	Tasks	Status
Using Kaldi for Automatic Speech Recognition of Conversational Austrian German	Jan 16, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using Large Language Model for End-to-End Chinese ASR and NER	Jan 21, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using multiple ASR hypotheses to boost i18n NLU performance	Dec 7, 2020	Abstractive Text SummarizationAutomatic Speech Recognition	—Unverified
Using multi-task learning to improve the performance of acoustic-to-word and conventional hybrid models	Feb 2, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using Related Languages to Enhance Statistical Language Models	Jun 1, 2016	Automatic Speech Recognition (ASR)Domain Adaptation	—Unverified
Using Spoken Word Posterior Features in Neural Machine Translation	Oct 1, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using Synthetic Audio to Improve The Recognition of Out-Of-Vocabulary Words in End-To-End ASR Systems	Nov 23, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using Text Injection to Improve Recognition of Personal Identifiers in Speech	Aug 14, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation	May 1, 2016	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models	Dec 13, 2023	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