2014 19th International Conference on Digital Signal Processing最新文献

A novel bimodal biometric identification system based on finger geometry and palm print 一种基于手指几何和掌纹的新型双峰生物识别系统

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900730

M. Anitha, K. A. R. Rao

引用次数: 3

Image deblurring using a pyramid-based Richardson-Lucy algorithm 使用基于金字塔的理查森-露西算法进行图像去模糊

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900829

Jian-Jiun Ding, Wei-De Chang, Yu Chen, Szu-Wei Fu, Chir-Weei Chang, Chuan-Chung Chang

引用次数: 8

Car number plate recognition for smart building management 汽车车牌识别智能楼宇管理

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900802

A. Visvanathan, T. Chattopadhyay

引用次数: 5

Improved Voice Activity Detection based on support vector machine with high separable speech feature vectors 基于支持向量机的高可分离语音特征向量改进语音活动检测

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900767

Y. Zou, W. Zheng, Wei Shi, Hong Liu

{"title":"Improved Voice Activity Detection based on support vector machine with high separable speech feature vectors","authors":"Y. Zou, W. Zheng, Wei Shi, Hong Liu","doi":"10.1109/ICDSP.2014.6900767","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900767","url":null,"abstract":"Voice Activity Detection (VAD) is one of the key techniques for many speech applications. Existing VAD algorithms have shown unsatisfied performance under nonstationary noise and low Signal-to-Noise-Ratio (SNR) situations. Motivated by the fact that people is able to distinguish the speech and non-speech even in low SNR situations, this paper studies the VAD technique from the pattern recognition point of view, where the VAD essentially is formulated as a binary classification problem. Specifically, the VAD is implemented by classifying the speech signal into speech and non-speech segments. The radial basis function (RBF) based support vector machine (SVM) is employed with supervised manner, which is perfectly suitable for binary classification tasks with some training samples. Aiming at achieving improved accuracy and robustness of the VAD technique to noise, the feature selection has been conducted by introducing the class separation measure (CSM) criterion to evaluate the capability of the feature vectors extracted for classifying speech and non-speech segments. Most famous speech features have been taken into account, including Mel-frequency cepstral coefficients (MFCC), the principal component analysis of the MFCC (PCA-MFCC), linear predictive coding (LPC) and linear predictive cepstral coding (LPCC). Intensive experimental results show that the MFCC features capture the most relevant information of speech and keep good separability of classification in different noisy conditions, so do the PCA-MFCC features. Moreover, the PCA-MFCC features are more robust to the noise with less computational cost. As a result, a VAD method by using the PCA-MFCC and the RBF-SVM as the classifier has been developed, which is termed as PCA-SVM-VAD for short. The experimental results with the NOIZEUS database show that the proposed PCA-SVM-VAD method has clear improvements over other VAD methods and performs much more robust in car noisy environment at various SNRs.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125119662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Investigating experienced quality factors in synthesized multi-view stereo images 研究合成多视点立体图像质量影响因素

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900729

Hak Gu Kim, Yong Ju Jung, S. Yoon, Yong Man Ro

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引用次数: 4

Non user interaction content summarization 非用户交互内容摘要

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900672

S. S. Thomas, Sumana Gupta, K. Venkatesh

引用次数: 3

Statistical analysis of temporal coherence function and its application in howling detection 时间相干函数的统计分析及其在嚎叫检测中的应用

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900789

C. Zheng, Yuxuan Ke, Renhua Peng, Xiaodong Li, Yi Zhou

引用次数: 0

Multiuser detection for MIMO DS-CDMA system in impulsive noise over Nakagami-m fading channels MIMO DS-CDMA系统在Nakagami-m衰落信道脉冲噪声下的多用户检测

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900674

S. R. Vempati, H. Khan, V. K. Pamula, A. K. Tipparti

引用次数: 0

Wideband spectrum sensing based on group testing utilizing polyphase filter banks 基于多相滤波器组组测试的宽带频谱传感

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900733

Shilian Zheng, Xiaoniu Yang

引用次数: 3

A new method for false-positive reduction in detection of lung nodules in CT images 一种新的肺结节CT检测假阳性降低方法

2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900710

Guo Cao, Yazhou Liu, Kenji Suzuki

引用次数: 5