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 1341–1350 of 3012 papers

Title	Date	Tasks	Status
Factual Consistency Oriented Speech Recognition	Feb 24, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Hierarchical Sequence to Sequence Voice Conversion with Limited Data	Jul 15, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
CAFE A Novel Code switching Dataset for Algerian Dialect French and English	Nov 20, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation	Feb 16, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Arabic Code-Switching Speech Recognition using Monolingual Data	Jul 4, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Highland Puebla Nahuatl Speech Translation Corpus for Endangered Language Documentation	Jun 1, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Facetron: A Multi-speaker Face-to-Speech Model based on Cross-modal Latent Representations	Jul 26, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
High-precision Voice Search Query Correction via Retrievable Speech-text Embedings	Jan 8, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Hindi-English Code-Switching Speech Corpus	Sep 24, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Byte Pair Encoding Is All You Need For Automatic Bengali Speech Recognition	Jan 28, 2024	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