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 1631–1640 of 3012 papers

Title	Date	Tasks	Status
Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts	Sep 25, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation	Sep 21, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
iRNN: Integer-only Recurrent Neural Network	Sep 20, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Audio-Visual Speech Recognition is Worth 32328 Voxels	Sep 20, 2021	Audio-Visual Speech RecognitionAutomatic Speech Recognition	—Unverified
MeetDot: Videoconferencing with Live Translation Captions	Sep 20, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Model-Based Approach for Measuring the Fairness in ASR	Sep 19, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Multimodal Audio-textual Architecture for Robust Spoken Language Understanding	Sep 17, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
PDAugment: Data Augmentation by Pitch and Duration Adjustments for Automatic Lyrics Transcription	Sep 16, 2021	Automatic Lyrics TranscriptionAutomatic Speech Recognition	—Unverified
Utterance-level neural confidence measure for end-to-end children speech recognition	Sep 16, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Improving Accent Identification and Accented Speech Recognition Under a Framework of Self-supervised Learning	Sep 15, 2021	Accented Speech RecognitionAutomatic 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