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 1721–1730 of 3012 papers

Title	Date	Tasks	Status
SpliceOut: A Simple and Efficient Audio Augmentation Method	Sep 30, 2021	Audio ClassificationAutomatic Speech Recognition	—Unverified
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Understanding the Role of Self Attention for Efficient Speech Recognition	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
W-CTC: a Connectionist Temporal Classification Loss with Wild Cards	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Synthesising Audio Adversarial Examples for Automatic Speech Recognition	Sep 29, 2021	Audio SynthesisAutomatic Speech Recognition	—Unverified
PhaseFool: Phase-oriented Audio Adversarial Examples via Energy Dissipation	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
MLP-based architecture with variable length input for automatic speech recognition	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition	Sep 29, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Conditioning Sequence-to-sequence Networks with Learned Activations	Sep 29, 2021	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