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 2751–2760 of 3012 papers

Title	Date	Tasks	Status
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition	Nov 15, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Phonemic and Graphemic Multilingual CTC Based Speech Recognition	Nov 13, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Multilingual Speech Recognition With A Single End-To-End Model	Nov 6, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Dual Language Models for Code Switched Speech Recognition	Nov 3, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Unsupervised Method for Improving Arabic Speech Recognition Systems	Nov 1, 2017	Arabic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Joint Learning of Dialog Act Segmentation and Recognition in Spoken Dialog Using Neural Networks	Nov 1, 2017	Automatic Speech Recognition (ASR)Natural Language Understanding	—Unverified
Improving Black-box Speech Recognition using Semantic Parsing	Nov 1, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Parallel Recurrent Neural Network for Language Modeling with POS Tags	Nov 1, 2017	Automatic Speech Recognition (ASR)Clustering	—Unverified
Sequence-to-Sequence ASR Optimization via Reinforcement Learning	Oct 30, 2017	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Study of All-Convolutional Encoders for Connectionist Temporal Classification	Oct 28, 2017	AllAutomatic Speech Recognition	—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