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2015 ISCA International Workshop on Speech and Language Technology in Education, SLaTE 2015

作者： Hönig, Florian Batliner, Anton Nöth, Elmar Pattern Recognition Lab FAU Erlangen-Nuremberg Germany Machine Intelligence and Signal Processing Group TUM Munich Germany

We present an in-depth analysis of a method for automatically scoring the prosody of non-native speech. For studying its suitability for different application scenarios, we perform a systematic comparison of different evaluation schemes such as text (in-)dependence and/or speaker (in-)dependence. The focus lies on methodological issues, with the aim of promoting the careful evaluation of automatic assessment methods. Further contributions are the analysis of (1) a method that utilizes speaker IDs to improve performance, and (2) the analysis of performance as a function of the number of speakers and texts used for training the system. Copyright © 2015 ISCA.

关键词： Speech communication

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Pinpointing the Difference – Visual Comparison of Non-Native Speaker Groups

Pinpointing the Difference – Visual Comparison of Non-Nativ...

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2015 ISCA International Workshop on Speech and Language Technology in Education, SLaTE 2015

作者： Hönig, Florian Wankerl, Sebastian Batliner, Anton Nöth, Elmar Pattern Recognition Lab FAU Erlangen-Nuremberg Germany Machine Intelligence and Signal Processing Group TUM Munich Germany

We apply a tool originally developed for comparing pathological and healthy speakers to non-native speech. The method works on speakers who produce a given word sequence. Using time-alignment, we can display prototypical loudness contours, local tempo variations, and also spectrograms, together with information on variability and group effect size over time. The system, which will be made publicly available, is able to expose typical differences in a group of German and Italian speakers. Copyright © 2015 ISCA.

关键词： Speech communication

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A new weighted anisotropic total variation algorithm for limited angle tomography

A new weighted anisotropic total variation algorithm for lim...

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IEEE International Symposium on Biomedical Imaging

作者： Y. Huang O. Taubmann X. Huang V Haase G. Lauritsch A. Maier Friedrich-Alexander-University Erlangen-Nuremberg Pattern Recognition Lab Erlangen Germany Siemens Healthcare GmbH Forchheim Germany University of Luebeck Institute for Signal Processing Luebeck Germany Erlangen Graduate School in Advanced Optical Technologies (SAOT) Erlangen Germany

ISBN: (纸本)9781479923519

This paper addresses streak reduction in limited angle tomography. The weighted total variation (wTV) algorithm is able to remove most Poisson noise and small streaks for clinical limited angle data. However, it is still not sufficient to remove larger streaks whose orientations are mostly dependent on the scan trajectory. We propose a new weighted anisotropic total variation (waTV) algorithm, which uses four neighboring pixels to calculate the gradient along the streaks' normal direction and is able to reduce large streaks well.

关键词： Image reconstruction Phantoms Computed tomography TV Minimization Bones

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Head rotation classification using dense motion estimation and particle filter tracking

Head rotation classification using dense motion estimation a...

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International Conference on Electrical and Electronics Engineering, ELECO

作者： Filiz Gürkan Bilge Günsel Deniz Kumlu Multimedia Signal Processing and Pattern Recognition Group Istanbul Technical University Turkey

We propose a method that performs dense motion classification integrated with particle filter tracking for monitoring whether the viewer is involved in the screened content or not. We first perform the color based particle filtering that enables us tracking head of the user through the video sequence. It is followed by optical flow estimation via SIFT flow applied on the tracked regions. Finally the features extracted based on the viewer head rotation and location are fed into the random forest classifier to report the involvement level of the tracked person. It is shown that the used probabilistic motion estimation model with the support of tracking significantly reduces the computational complexity while it provides comparable performance with the state-of-the-art methods. The proposed scheme allows online monitoring the viewer therefore can be integrated to the interactive multimedia systems.

关键词： Head Image motion analysis Computer vision Tracking Particle filters Magnetic heads Motion estimation

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Binary pattern flavored feature extractors for Facial Expression recognition: An overview

Binary pattern flavored feature extractors for Facial Expres...

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Proceedings of the International Convention MIPRO

作者： Rasmus Lyngby Kristensen Zheng-Hua Tan Zhanyu Ma Jun Guo Section of Image Analysis and Computer Graphics Technical University of Denmark Kgs. Lyngby Denmark Signal and Information Processing section (SIP) Aalborg University Aalborg Denmark Pattern Recognition and Intelligent System Lab. Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781479981748

This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER terminology, describes open challenges, and provides recommendations to scientific evaluation of FER systems. Lastly, it studies the facial expression recognition accuracy and blur invariance of the Local Frequency Descriptor. The paper seeks to bring together disjointed studies, and the main contribution is to provide a solid overview for future research.

关键词： Feature extraction Face Face recognition Databases Three-dimensional displays Accuracy Gold

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Comparison of appearance-based and geometry-based bubble detectors

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8671卷 610-617页

作者： Strokina, Nataliya Juránek, Roman Eerola, Tuomas Lensu, Lasse Zemčik, Pavel Kälviäinen, Heikki Tampere University of Technology Department of Signal Processing P.O. Box 527 Tampere33101 Finland Brno University of Technology Department of Computer Graphics and Multimedia Brno Czech Republic Lappeenranta University of Technology Machine Vision and Pattern Recognition Laboratory P.O. Box 20 Lappeenranta53851 Finland

Bubble detection is a complicated tasks since varying lighting conditions changes considerably the appearance of bubbles in liquid. The two common techniques to detect circular objects such as bubbles, the geometry-based and appearance-based approaches, have their advantages and weaknesses. The geometry-based methods often fail to detect small blob-like bubbles that do not match the used geometrical model, and appearance-based approaches are vulnerable to appearance changes caused by, e.g., illumination. In this paper, we compare a geometry-based concentric circular arrangements (CCA) and appearance-based sliding window methods as well as their combinations in terms of bubble detection, gas volume computation, and size distribution estimation. The best bubble detection performance was achieved with the sliding window method whereas the most precise volume estimate was produced by the CCA method. The combination of the two approaches gave only a minor advantage compared to the base methods. © Springer International Publishing Switzerland 2014.

关键词： Geometry

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SAR IMAGE CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTURES

SAR IMAGE CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTU...

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IEEE International Conference on Image processing

作者： Koray Kayabol Bilge Gunsel Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University

ISBN: (纸本)9781479923427

We propose a novel image prior for the non-parametric Bayesian mixture model based unsupervised classification of SAR images. We modified the Normalized Gamma Process prior that constitutes a more general form of the Dirichlet Process prior in order to enclose the contribution of the adjacent pixels into the classification scheme. This yields an image classification prior embedded in a mixture model that allows infinite number of clusters and enables reaching to smoothed classification maps. Based on the classification results obtained on synthetic and real TerraSAR-X images, it is shown that the proposed model is capable of accurately classifying the pixels. It applies a simple iterative update scheme at a single run without performing a hierarchical clustering strategy as used in the previously proposed methods. It is also demonstrated that the model order estimation accuracy of the proposed method outperforms the conventional finite mixture models.

关键词： Infinite mixture models Normalized gamma process mixtures Nonparametric Bayesian Image classification SAR images Image classification Mixture models images Radar polarimetry classification scheme pixel Rescue Synthetic aperture radar Specific absorption rate SAFETY ANALYSIS REPORTS mixtures

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SLEEPINESS DETECTION FROM SPEECH BY PERCEPTUAL FEATURES

SLEEPINESS DETECTION FROM SPEECH BY PERCEPTUAL FEATURES

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IEEE International Conference on Acoustics, Speech and signal processing

作者： Bilge Gunsel Cenk Sezgin Jarek Krajewski Multimedia Signal Processing and Pattern Recognition Group Istanbul Technical Univ. Turkey Experimental Industrial Psychology Univ. of Wuppertal Germany

ISBN: (纸本)9781479903573

We propose a two-class classification scheme with a small number of features for sleepiness detection. Unlike the conventional methods that rely on the linguistics content of speech, we work with prosodic features extracted by psychoacoustic masking in spectral and temporal domain. Our features also model the variations between non-sleepy and sleepy modes in a quasi-continuum space with the help of code words learned by a bag-of-features scheme. These improve the unweighted recall rates for unseen people and minimize the language dependence. Recall rates reported based on Karolinska Sleepiness Scale (KSS) for Support Vector Machine and Learning Vector Quantization classifiers show that the developed system enables us monitoring sleepiness efficiently with a lower complexity compared to the reported benchmarking results for Sleepy Language Corpus.

关键词： Speech Sleepiness Linguistics Pragmatics Support Vector Network Retrieval recall codeword recall Mental Recall quasi-continuum learning vector quantization

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AN ADAPTIVE TIME-FREQUENCY RESOLUTION FRAMEWORK FOR SINGLE CHANNEL SOURCE SEPARATION BASED ON NON-NEGATIVE TENSOR FACTORIZATION

AN ADAPTIVE TIME-FREQUENCY RESOLUTION FRAMEWORK FOR SINGLE C...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： S. Kirbiz B. Gunsel Multimedia Signal Processing and Pattern Recognition Group. Dept. of Electronics and Comm. Eng. Istanbul Technical University Turkey

ISBN: (纸本)9781479903573

In this paper, we propose an adaptive time-frequency resolution based single channel sound source separation method using Non-negative Tensor Factorization (NTF). The model aims to alleviate drawbacks of working by fixed length Short Time Fourier Transform (STFT) by minimizing the smearing of signal energy in both time and frequency. A joint optimization scheme has been applied based on KL-divergence where each layer of the tensor represents the mixture at a different resolution. In order to enclose sparseness into factorization, the resynthesis is made through an adaptive weighted fusion procedure which combines the separated sources in a manner that maximizes the energy concentration. Test results reported over a large sound database indicate the introduced NTF based fusion method improves the sound quality both in terms of conventional and perceptual distortion measures.

关键词： Tensor factorization Perceptual Distortion STFT fusion procedure signal energy Resolving power Voice Quality fusion method frequency resolution

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Perceptually weighted Non-negative Matrix Factorization for blind single-channel music source separation

Perceptually weighted Non-negative Matrix Factorization for ...

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International Conference on pattern recognition

作者： S. Kırbız B. Gunsel Multimedia Signal Processing and Pattern Recognition Laboratory Department of Electronics and Communications Engineering Technical University Maslak Istanbul Turkey

We propose a blind single-channel musical source separation method that improves perceptual quality of the separated sources. It uses the advantages of subspace learning based on Non-negative Matrix Factor 2-D Deconvolution (NMF2D). To improve the perceptual quality of separation, we propose a weighted divergence type cost function for the optimization that adopts the auditory model defined in ITU-R BS.1387 into the source separation. It is shown that the proposed perceptually weighted NMF2D scheme efficiently clusters the bases of subspace representation corresponding to notes generated by single instruments. Source separation performance has been reported on musical mixtures resulting an improvement in perceptual quality measures.

关键词： Source separation Spectrogram Time frequency analysis Instruments Humans Time domain analysis Computational complexity

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