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 2981–2990 of 3012 papers

Title	Date	Tasks	Status
Code-Switching Text Generation and Injection in Mandarin-English ASR	Mar 20, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Collaborative Data Relabeling for Robust and Diverse Voice Apps Recommendation in Intelligent Personal Assistants	Nov 1, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Combining Human Inputters and Language Services to provide Multi-language support system for International Symposiums	Dec 1, 2016	Automatic Speech Recognition (ASR)Machine Translation	—Unverified
Combining Spectral and Self-Supervised Features for Low Resource Speech Recognition and Translation	Apr 5, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Combining X-Vectors and Bayesian Batch Active Learning: Two-Stage Active Learning Pipeline for Speech Recognition	May 3, 2024	Active LearningAutomatic Speech Recognition	—Unverified
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition	Jan 24, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voice	May 29, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Communication-Efficient Personalized Federated Learning for Speech-to-Text Tasks	Jan 18, 2024	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Comparative Analysis of the wav2vec 2.0 Feature Extractor	Aug 8, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Comparing Apples to Oranges: LLM-powered Multimodal Intention Prediction in an Object Categorization Task	Apr 12, 2024	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