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 1481–1490 of 3012 papers

Title	Date	Tasks	Status
Probing Speech Emotion Recognition Transformers for Linguistic Knowledge	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Text-To-Speech Data Augmentation for Low Resource Speech Recognition	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Alternate Intermediate Conditioning with Syllable-level and Character-level Targets for Japanese ASR	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Multi-task RNN-T with Semantic Decoder for Streamable Spoken Language Understanding	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
End-to-End Multi-speaker ASR with Independent Vector Analysis	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
End-to-End Integration of Speech Recognition, Speech Enhancement, and Self-Supervised Learning Representation	Apr 1, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Effectiveness of text to speech pseudo labels for forced alignment and cross lingual pretrained models for low resource speech recognition	Mar 31, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Comparative Study on Speaker-attributed Automatic Speech Recognition in Multi-party Meetings	Mar 31, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition	Mar 31, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Memory-Efficient Training of RNN-Transducer with Sampled Softmax	Mar 31, 2022	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