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Chinese Accents Identification with Modified MFCC
2012It is well known that performance of Chinese speech recognition system fluctuates sharply with variation of accents. Hence it is feasible to identify accents before recognition. Based on our previous analysis [1], it is discovered that the first two formants are more sensitive to Chinese accents than others.
Qin Yan, Zhengjuan Zhou, Shan Li
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Speech emotion recognition using MFCC-based entropy feature
Signal, Image and Video Processing, 2023Siba Prasad Mishra +2 more
exaly
Retracted: Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy
2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI), 2015Priyanka Bansal +2 more
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Retraction Notice: Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy
2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI), 2015Priyanka Bansal +2 more
openaire +1 more source
Speaker normalization in the MFCC domain
6th International Conference on Spoken Language Processing (ICSLP 2000), 2000openaire +1 more source
Evaluation and modeling of automotive transmission whine noise quality based on MFCC and CNN
Applied Acoustics, 2021Xiufeng Wang, Dan He
exaly
Vocal tract normalization as linear transformation of MFCC
8th European Conference on Speech Communication and Technology (Eurospeech 2003), 2003Michael Pitz, Hermann Ney
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MLP network for enhancement of noisy MFCC vectors
6th European Conference on Speech Communication and Technology, 1999Hemmo Haverinen +4 more
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