Results 131 to 140 of about 839 (154)

Robust speaker recognition based on improved GFCC

2016 2nd IEEE International Conference on Computer and Communications (ICCC), 2016
Focused on the issue that the robustness of traditional Mel Frequency Cepstral Coefficients (MFCC) feature degrades drastically in speaker recognition system, a kind algorithm that based improved Gammatone Frequency Cepstral Coefficients (GFCC) is proposed.
null Xiaoyuan Shi, null Haiyan Yang, null Ping Zhou   +2 more
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Research on Failure Identification of Partial Discharge Ultrasonic Signal Based on GFCC

2020 IEEE Electrical Insulation Conference (EIC), 2020
Traditional on-line detection of partial discharge based on ultrasonic method has become an important means to detect the insulation condition of electrical equipment. However, most of its detection is based on the threshold value to realize the function similar to “traffic light”, that is, to detect whether partial discharge occurs or not.
Zhou Mengxi, Tang Zhiguo
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New Feature Vectors using GFCC for Speaker Identification

International Journal of Emerging Research in Management and Technology, 2018
The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set
Dr. A. Nagesh
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Feature extraction algorithm fusing GFCC and phase information

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017
For the traditional Mel cepstral coefficient feature extraction method is not completely in line with the characteristics of human audition, an auditory feature extraction algorithm based on Gamma-chirp filter cepstrum coefficient and phase information is proposed.
Yi Zhang, Lei Ni
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GFCC: A Global Fast Congestion Control Mechanism Based on Software-Defined Networking

IEEE Transactions on Networking
With the rapid growth of cloud computing, datacenter networks (DCNs) are facing escalating congestion challenges due to high-bandwidth, low-latency applications. Existing congestion control methods based on Explicit Congestion Notification (ECN) or delay
Hongxiang Wang, Yifei Lu 0001, Zhen Wang
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Underwater acoustic target classification based on modified GFCC features

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017
A major challenge for underwater acoustic target classification relates to significant performance decrease in complex underwater environment. Recent researches have shown that the auditory feature extracted from Gammatone filter has remarkable ability on robust speaker identification.
Zixu Lian, Ke Xu, Jianwei Wan, Gang Li
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Acoustic Feature Extraction of Wind Turbine Blades Based on Improved MFCC-GFCC

2024 IEEE 22nd International Conference on Industrial Informatics (INDIN)
As a critical component of wind turbines, the structural integrity of the blades is crucial for safe operation. To enhance the performance of health monitoring and fault detection systems, an acoustic feature extraction method is proposed to designed to ...
Ziyi Wang, Yuanye Chen, Hua Wang, Haichao Wang, Fang Fang 0007   +4 more
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A robust Speaker Identification System based on the combination of GFCC and MFCC methods

2016 5th International Conference on Multimedia Computing and Systems (ICMCS), 2016
The performances of Speaker Identification Systems (SIS) are strongly influenced by the quality and quantity of the used speech signal. Most of these systems are based on Gaussian Mixture Models (GMM) that is trained using a training speech database.
E. Tazi
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GFCC based discriminatively trained noise robust continuous ASR system for Hindi language

Journal of Ambient Intelligence and Humanized Computing, 2018
A statistically designed Automatic Speech Recognition (ASR) system extracts features from speech signals using feature extraction methods, links the extracted features with the expected phonetics of the hypothesis using acoustic models, uses language model to add prior information about the structure of the target language.
Mohit Dua, Rajesh Kumar Aggarwal, Mantosh Biswas   +2 more
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Dialect recognition based on improved GFCC with VMD and Teager energy operator cepstral coefficients

Sixteenth International Conference on Signal Processing Systems (ICSPS 2024)
Aiming at the problems of low recognition rate of Chinese dialects and poor robustness in noisy environment, this paper proposes an improved feature extraction algorithm, which combines the Sparrow Search Algorithm (SSA) and Variational Mode ...
Liyan Zhang, Chao Qi, Zengli Liu, Xuanzhi Zhao, Shaowei Rong   +4 more
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