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 1421–1430 of 3012 papers

Title	Date	Tasks	Status
MLP-ASR: Sequence-length agnostic all-MLP architectures for speech recognition	Feb 17, 2022	AllAutomatic Speech Recognition	—Unverified
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers	Feb 16, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Conversational Speech Recognition By Learning Conversation-level Characteristics	Feb 16, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
ADIMA: Abuse Detection In Multilingual Audio	Feb 16, 2022	Abuse DetectionAutomatic Speech Recognition	CodeCode Available
Multi-style Training for South African Call Centre Audio	Feb 15, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme	Feb 14, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Multimodal Depression Classification Using Articulatory Coordination Features And Hierarchical Attention Based Text Embeddings	Feb 13, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding	Feb 10, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available
Enhancing ASR for Stuttered Speech with Limited Data Using Detect and Pass	Feb 8, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A two-step approach to leverage contextual data: speech recognition in air-traffic communications	Feb 8, 2022	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