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 2111–2120 of 3012 papers

Title	Date	Tasks	Status
Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognition	Jan 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition	Oct 21, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline	Jun 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Talk, Don't Write: A Study of Direct Speech-Based Image Retrieval	Apr 5, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Targeted Adversarial Examples for Black Box Audio Systems	Oct 22, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS	Jun 10, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Task-aware Warping Factors in Mask-based Speech Enhancement	Aug 27, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Teach an all-rounder with experts in different domains	Jul 9, 2019	AllAutomatic Speech Recognition	—Unverified
Technology-Augmented Multilingual Communication Models: New Interaction Paradigms, Shifts in the Language Services Industry, and Implications for Training Programs	Aug 1, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
TED-LIUM: an Automatic Speech Recognition dedicated corpus	May 1, 2012	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