2D Psychoacoustic modeling of equivalent masking for automatic speech recognition

Author:

Dai PengORCID,Rudzicz Frank,Soon Ing Yann,Mihailidis Alex,Ding Huijun

Funder

National Natural Science Foundation of China

Guangdong Natural Science Foundation

Shenzhen Science and Technology Innovation Fund

Natural Science Foundation of SZU

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference30 articles.

1. Digital Processing of Speech Signals;Rabiner,1978

2. H. Ding, Speech enhancement in transform domain (Ph.D. thesis), Nanyang Technological University, 2011.

3. Automatic speech recognition and speech variability;Benzeghiba;Speech Commun.,2007

4. P. Dai, Speech recognition based on front-end noise removal algorithms (Ph.D. thesis), Nanyang Technological University, 2014.

5. L. Deng, G.E. Hinton, B. Kingsbury, New types of deep neural network learning for speech recognition and related applications: an overview, in IEEE IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, Vancouver, BC, Canada, 2013, 8599–8603

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1. FEATURE EXTRACTION ALGORITHM USING NEW CEPSTRAL TECHNIQUES FOR ROBUST SPEECH RECOGNITION;Malaysian Journal of Computer Science;2020-04-24

2. PSYCHOACOUSTICAL MASKING EFFECT-BASED FEATURE EXTRACTION FOR ROBUST SPEECH RECOGNITION;INT J INNOV COMPUT I;2019

3. A critical review and analysis on techniques of speech recognition: The road ahead;International Journal of Knowledge-based and Intelligent Engineering Systems;2018-03-21

4. Novel Speech Processing Algorithm for Perception Improvement and Needed Research for Hearing Impaired;Proceedings of the International Conference on Data Engineering and Communication Technology;2016-08-24

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