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Whisper intelligibility enhancement based on noise robust feature and SVM 被引量:2
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作者 周健 赵力 +1 位作者 梁瑞宇 方贤勇 《Journal of Southeast University(English Edition)》 EI CAS 2012年第3期261-265,共5页
A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine (SVM) classifier is used to synthesize... A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine (SVM) classifier is used to synthesize the enhanced whisper. A novel noise robust feature called Gammatone feature cosine coefficients (GFCCs) extracted by an auditory periphery model is derived and used for the binary mask estimation. The intelligibility performance of the proposed method is evaluated and compared with the traditional speech enhancement methods. Objective and subjective evaluation results indicate that the proposed method can effectively improve the intelligibility of whispered speech which is contaminated by noise. Compared with the power subtract algorithm and the log-MMSE algorithm, both of which do not improve the intelligibility in lower signal-to-noise ratio (SNR) environments, the proposed method has good performance in improving the intelligibility of noisy whisper. Additionally, the intelligibility of the enhanced whispered speech using the proposed method also outperforms that of the corresponding unprocessed noisy whispered speech. 展开更多
关键词 whispered speech intelligibility enhancement noise robust feature machine learning
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Speech Intelligibility Enhancement Algorithm Based on Multi-Resolution Power-Normalized Cepstral Coefficients(MRPNCC)for Digital Hearing Aids
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作者 Xia Wang Xing Deng +2 位作者 Hongming Shen Guodong Zhang Shibing Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第2期693-710,共18页
Speech intelligibility enhancement in noisy environments is still one of the major challenges for hearing impaired in everyday life.Recently,Machine-learning based approaches to speech enhancement have shown great pro... Speech intelligibility enhancement in noisy environments is still one of the major challenges for hearing impaired in everyday life.Recently,Machine-learning based approaches to speech enhancement have shown great promise for improving speech intelligibility.Two key issues of these approaches are acoustic features extracted from noisy signals and classifiers used for supervised learning.In this paper,features are focused.Multi-resolution power-normalized cepstral coefficients(MRPNCC)are proposed as a new feature to enhance the speech intelligibility for hearing impaired.The new feature is constructed by combining four cepstrum at different time–frequency(T–F)resolutions in order to capture both the local and contextual information.MRPNCC vectors and binary masking labels calculated by signals passed through gammatone filterbank are used to train support vector machine(SVM)classifier,which aim to identify the binary masking values of the T–F units in the enhancement stage.The enhanced speech is synthesized by using the estimated masking values and wiener filtered T–F unit.Objective experimental results demonstrate that the proposed feature is superior to other comparing features in terms of HIT-FA,STOI,HASPI and PESQ,and that the proposed algorithm not only improves speech intelligibility but also improves speech quality slightly.Subjective tests validate the effectiveness of the proposed algorithm for hearing impaired. 展开更多
关键词 Speech intelligibility enhancement multi-resolution power-normalized cepstral coefficients binary masking value hearing impaired
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Real- Time Color Enhancement Method Used for Intelligent Mobile Terminals
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作者 Jin Hui (Solution Marketing Department of Product Marketing System, ZTE Corporation, Shenzhen 518057, P. R. China) 《ZTE Communications》 2009年第4期49-53,共5页
In certain environments and under some conditions, the video images taken by the intelligent mobile video phones seem dark, and the colors are not bright or saturated enough.This paper presents an adaptive method to e... In certain environments and under some conditions, the video images taken by the intelligent mobile video phones seem dark, and the colors are not bright or saturated enough.This paper presents an adaptive method to enhance the video image brightness visualization and the color performance depending on the certain hardware property and function parameters. The experimental results prove that this method can enhance the colors and the contrast of the video images, based on the estimated quality feature values of each frame, without using the extra Digital Signal Processor (DSP). 展开更多
关键词 YUV Time Color enhancement Method Used for Intelligent Mobile Terminals REAL FIGURE
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New endoscopic approaches in IBD 被引量:6
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作者 Helmut Neumann Markus F Neurath Jonas Mudter 《World Journal of Gastroenterology》 SCIE CAS CSCD 2011年第1期63-68,共6页
Recent advances in endoscopic imaging techniques have revolutionized the diagnostic approach of patients with inflammatory bowel disease(IBD).New,emerging endoscopic imaging techniques visualized a plethora of new muc... Recent advances in endoscopic imaging techniques have revolutionized the diagnostic approach of patients with inflammatory bowel disease(IBD).New,emerging endoscopic imaging techniques visualized a plethora of new mucosal details even at the cellular and subcellular level.This review offers an overview about new endoscopic techniques,including chromoendoscopy,magnification endoscopy,spectroscopy,confocal laser endomicroscopy and endocytoscopy in the face of IBD. 展开更多
关键词 ENDOSCOPY Inflammatory bowel disease ENDOMICROSCOPY ENDOCYTOSCOPY Narrow band imaging Fujinon intelligent color enhancement i-Scan Spectroscopy CHROMOENDOSCOPY Ulcerative colitis Crohn's disease Fluorescence endoscopy
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System Strength Assessment Based on Multi-task Learning
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作者 Baoluo Li Shiyun Xu +2 位作者 Huadong Sun Zonghan Li Lin Yu 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2024年第1期41-50,共10页
Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practica... Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable range.Therefore,a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven method.First,calculation of critical short circuit ratio(CSCR)is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative indicator.Then,the construction process of CSCR dataset is proposed,and a batch simulation program of samples is developed accordingly,which provides a data basis for subsequent research.Finally,a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point,which significantly reduces evaluation error caused by weak links.Predictive performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system,which provides strong technical support for real-time monitoring of system strength. 展开更多
关键词 Critical short circuit ratio hybrid intelligence enhancement multi-task learning system strength
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