2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)最新文献_第8页

Constant False Alarm Rate for Online one Class Svm Learning 在线一类Svm学习的恒定虚警率

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8462022

Yongjian Xue, P. Beauseroy

引用次数: 1

Low-Overhead Receiver-Side Channel Tracking for Mmwave Mimo 毫米波Mimo的低开销接收机侧信道跟踪

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8461320

Karthik Upadhya, S. Vorobyov, R. Heath

引用次数: 2

On Compressive Sensing of Sparse Covariance Matrices Using Deterministic Sensing Matrices 基于确定性感知矩阵的稀疏协方差矩阵压缩感知研究

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8461312

Alihan Kaplan, V. Pohl, Dae Gwan Lee

引用次数: 4

Robust and Effective Hyperspectral Pansharpening Using Spatio-Spectral Total Variation 基于空间光谱全变分的鲁棒有效高光谱泛锐化

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8462464

Saori Takeyama, Shunsuke Ono, I. Kumazawa

{"title":"Robust and Effective Hyperspectral Pansharpening Using Spatio-Spectral Total Variation","authors":"Saori Takeyama, Shunsuke Ono, I. Kumazawa","doi":"10.1109/ICASSP.2018.8462464","DOIUrl":"https://doi.org/10.1109/ICASSP.2018.8462464","url":null,"abstract":"Acquiring high-resolution hyperspectral (HS) images is a very challenging task. To this end, hyperspectral pansharpening techniques have been widely studied, which estimate an HS image of high spatial and spectral resolution (high HS image) from a pair of an HS image of high spectral resolution but low spatial resolution (low HS image) and a high spatial resolution panchromatic (PAN) image. However, since these methods do not fully utilize the piecewise-smoothness of spectral information on HS images in estimation, they tend to produce spectral distortion when the low HS image contains noise. To tackle this issue, we propose a new hyperspectral pansharpening method using a spatio-spectral regularization. Our method not only effectively exploits observed information but also properly promotes the spatio-spectral piecewise-smoothness of the resulting high HS image, leading to high quality and robust estimation. The proposed method is reduced to a nonsmooth convex optimization problem, which is efficiently solved by a primal-dual splitting method. Our experiments demonstrate the advantages of our method over existing hyperspectral pansharpening methods.","PeriodicalId":6638,"journal":{"name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"45 1","pages":"1603-1607"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86512694","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: 6

Comparison of Speech Tasks for Automatic Classification of Patients with Amyotrophic Lateral Sclerosis and Healthy Subjects 肌萎缩侧索硬化症患者与健康受试者语音自动分类任务的比较

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8461836

Aravind Illa, Deep Patel, B. Yamini, Meera ss, N. Shivashankar, P. Veeramani, Seena vengalii, Kiran Polavarapui, S. Nashi, A. Nalini, P. Ghosh

{"title":"Comparison of Speech Tasks for Automatic Classification of Patients with Amyotrophic Lateral Sclerosis and Healthy Subjects","authors":"Aravind Illa, Deep Patel, B. Yamini, Meera ss, N. Shivashankar, P. Veeramani, Seena vengalii, Kiran Polavarapui, S. Nashi, A. Nalini, P. Ghosh","doi":"10.1109/ICASSP.2018.8461836","DOIUrl":"https://doi.org/10.1109/ICASSP.2018.8461836","url":null,"abstract":"In this work, we consider the task of acoustic and articulatory feature based automatic classification of Amyotrophic Lateral Sclerosis (ALS) patients and healthy subjects using speech tasks. In particular, we compare the roles of different types of speech tasks, namely rehearsed speech, spontaneous speech and repeated words for this purpose. Simultaneous articulatory and speech data were recorded from 8 healthy controls and 8 ALS patients using AG501 for the classification experiments. In addition to typical acoustic and articulatory features, new articulatory features are proposed for classification. As classifiers, both Deep Neural Networks (DNN) and Support Vector Machines (SVM) are examined. Classification experiments reveal that the proposed articulatory features outperform other acoustic and articulatory features using both DNN and SVM classifier. However, SVM performs better than DNN classifier using the proposed feature. Among three different speech tasks considered, the rehearsed speech was found to provide the highest F-score of 1, followed by an F-score of 0.92 when both repeated words and spontaneous speech are used for classification.","PeriodicalId":6638,"journal":{"name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"46 15 1","pages":"6014-6018"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73471803","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: 20

Faster and Still Safe: Combining Screening Techniques and Structured Dictionaries to Accelerate the Lasso 更快，仍然安全:结合筛选技术和结构化词典加速套索

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8461514

C. Dantas, R. Gribonval

引用次数: 6

An Investigation of Subband Wavenet Vocoder Covering Entire Audible Frequency Range with Limited Acoustic Features 覆盖整个可听频率范围的有限声学特征子带波声编码器研究

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8462237

T. Okamoto, Kentaro Tachibana, T. Toda, Y. Shiga, H. Kawai

引用次数: 21

Online Education Evaluation for Signal Processing Course Through Student Learning Pathways 基于学生学习路径的信号处理课程在线教育评估

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8461464

K. H. Ng, S. Tatinati, Andy W. H. Khong

引用次数: 6

Epileptic State Segmentation with Temporal-Constrained Clustering 基于时间约束聚类的癫痫状态分割

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8462070

Kang Lin, Yu Qi, Shaozhe Feng, Qi Lian, Gang Pan, Yueming Wang

{"title":"Epileptic State Segmentation with Temporal-Constrained Clustering","authors":"Kang Lin, Yu Qi, Shaozhe Feng, Qi Lian, Gang Pan, Yueming Wang","doi":"10.1109/ICASSP.2018.8462070","DOIUrl":"https://doi.org/10.1109/ICASSP.2018.8462070","url":null,"abstract":"Automatic seizure identification plays an important role in epilepsy evaluation. Most existing methods regard seizure identification as a classification problem and rely on labelled training set. However, labelling seizure onset is very expensive and seizure data for each individual is especially limited, classifier-based methods are usually impractical in use. Clustering methods could learn useful information from unlabelled data, while they may lead to unstable results given epileptic signals with high noises. In this paper, we propose to use Gaussian temporal-constrained k-medoids method for seizure state segmentation. Using temporal information, the noises could be effectively suppressed and robust clustering performance is achieved. Besides, a new criterion called signed total variation (STV) which describes temporal integrity and consistency is proposed for temporal-constrained clustering evaluation. Experimental results show that, compared with the existing methods, the k-medoids method with Gaussian temporal constraint achieves the best results on both F1-score and STV.","PeriodicalId":6638,"journal":{"name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"881-885"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83501276","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: 0

A Deep Reinforcement Learning Framework for Identifying Funny Scenes in Movies 一种用于识别电影搞笑场景的深度强化学习框架

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2018-04-24 DOI: 10.1109/ICASSP.2018.8462686

Haoqi Li, Naveen Kumar, Ruxin Chen, P. Georgiou

引用次数: 14