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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2261–2270 of 3012 papers

Title	Date	Tasks	Status
Samr\'omur: Crowd-sourcing Data Collection for Icelandic Speech Recognition	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
CEASR: A Corpus for Evaluating Automatic Speech Recognition	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Phonemic Transcription of Low-Resource Languages: To What Extent can Preprocessing be Automated?	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Automatically Assess Children's Reading Skills	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
The SAFE-T Corpus: A New Resource for Simulated Public Safety Communications	May 1, 2020	Action DetectionActivity Detection	—Unverified
Large Vocabulary Read Speech Corpora for Four Ethiopian Languages: Amharic, Tigrigna, Oromo and Wolaytta	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Towards Building an Automatic Transcription System for Language Documentation: Experiences from Muyu	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Transfer Learning for Less-Resourced Semitic Languages Speech Recognition: the Case of Amharic	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition	May 1, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Automatic Speech Recognition for Uyghur through Multilingual Acoustic Modeling	May 1, 2020	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