Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

The European Position Paper on Rhinosinusitis and Nasal Polyps 2020 is the update of similar evidence based position papers published in 2005 and 2007 and 2012. The core objective of the EPOS2020 guideline is to provide revised, up-to-date and clear evidence-based recommendations and integrated care pathways in ARS and CRS. EPOS2020 provides an update on the literature published and studies undertaken in the eight years since the EPOS2012 position paper was published and addresses areas not extensively covered in EPOS2012 such as paediatric CRS and sinus surgery. EPOS2020 also involves new stakeholders, including pharmacists and patients, and addresses new target users who have become more involved in the management and treatment of rhinosinusitis since the publication of the last EPOS document, including pharmacists, nurses, specialised care givers and indeed patients themselves, who employ increasing self-management of their condition using over the counter treatments. The document provides suggestions for future research in this area and offers updated guidance for definitions and outcome measurements in research in different settings. EPOS2020 contains chapters on definitions and classification where we have defined a large number of terms and indicated preferred terms. A new classification of CRS into primary and secondary CRS and further division into localized and diffuse disease, based on anatomic distribution is proposed. There are extensive chapters on epidemiology and predisposing factors, inflammatory mechanisms, (differential) diagnosis of facial pain, allergic rhinitis, genetics, cystic fibrosis, aspirin exacerbated respiratory disease, immunodeficiencies, allergic fungal rhinosinusitis and the relationship between upper and lower airways. The chapters on paediatric acute and chronic rhinosinusitis are totally rewritten. All available evidence for the management of acute rhinosinusitis and chronic rhinosinusitis with or without nasal polyps in adults and children is systematically reviewed and integrated care pathways based on the evidence are proposed. Despite considerable increases in the amount of quality publications in recent years, a large number of practical clinical questions remain. It was agreed that the best way to address these was to conduct a Delphi exercise . The results have been integrated into the respective sections. Last but not least, advice for patients and pharmacists and a new list of research needs are included. The full document can be downloaded for free on the website of this journal: http://www.rhinologyjournal.com.

/pdf/european-position-paper-on-rhinosinusitis-and-nasal-polyps-mj734vsl7p.pdf

European Position Paper on Rhinosinusitis and Nasal Polyps 2020

Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this way, the dependence on a large number of target-domain data can be reduced for constructing target learners. Due to the wide application prospects, transfer learning has become a popular and promising area in machine learning. Although there are already some valuable and impressive surveys on transfer learning, these surveys introduce approaches in a relatively isolated way and lack the recent advances in transfer learning. Due to the rapid expansion of the transfer learning area, it is both necessary and challenging to comprehensively review the relevant studies. This survey attempts to connect and systematize the existing transfer learning research studies, as well as to summarize and interpret the mechanisms and the strategies of transfer learning in a comprehensive way, which may help readers have a better understanding of the current research status and ideas. Unlike previous surveys, this survey article reviews more than 40 representative transfer learning approaches, especially homogeneous transfer learning approaches, from the perspectives of data and model. The applications of transfer learning are also briefly introduced. In order to show the performance of different transfer learning models, over 20 representative transfer learning models are used for experiments. The models are performed on three different data sets, that is, Amazon Reviews, Reuters-21578, and Office-31, and the experimental results demonstrate the importance of selecting appropriate transfer learning models for different applications in practice.

A Comprehensive Survey on Transfer Learning

Independent Component Analysis.

In this paper, we study support vector machine based approaches for acoustic modeling of subword units in continuous speech. Classification of subword unit segments is considered as a multi-class pattern recognition problem. In conventional approaches for multi-class pattern recognition using support vector machines, learning involves discrimination of each class against all the other classes. We propose a close-class-set discrimination method suitable for large-class-set pattern recognition problems. In the proposed method, learning involves discrimination of each class against a subset of classes confusable with it and included in its close-class-set. We consider different criteria for identification of close-class-sets. We study the effectiveness of the proposed method in reducing the complexity of multiclass pattern recognition systems. We present our studies on recognition of continuous speech segments of 41 monophone units in a large corpus of Japanese speech.

Recognition of continuous speech segments of monophone units using support vector machines.

Smart Mobile In-Vehicle Systems

This paper describes a new method for estimating the direction of arrival (DOA) using a nonlinear microphone array based on complementary beamforming. Complementary beamforming is based on two types of beamformers designed to obtain complementary directivity patterns with each other. In this system, since the resultant directivity pattern is proportional to the product of these directivity patterns, the proposed method can be used to estimate DOAs even when the number of sound sources is equal to or exceeds that of microphones. First, DOA-estimation experiments are performed using actual devices in real acoustic environments. The results clarify that DOA estimation for two sound sources can be accomplished by the proposed method with only two microphones. Also, by comparing the resolutions of DOA estimation by the proposed method and by the conventional minimum variance method, we can show that the performance of the proposed method is superior to that of the conventional method.

Direction of arrival estimation based on nonlinear microphone array

In this work, we develop and compare noise suppression filtering systems based on maximum a posterior probability (MAP) and cumulative distribution function equalization (CDFE) estimation of speech spectrum. In these systems, we use a double-gamma modeling for both the speech and noise spectral components, in which the distributions are adapted to the actual parameters in each frequency bin. The performances of the proposed systems are tested using the Aurora database they are shown to be better than conventional systems derived from the MMSE method. Whereas the MAP-based method performed best in the SNR improvement, the CDFE-based system provides a lower musical noise level and shows a higher recognition rate.

Maximum a posterior probability and cumulative distribution function equalization methods for speech spectral estimation with application in noise suppression filtering

In this study, we investigate the effect of tiny acoustic differences on the efficiency of prosodic information transmission. Study participants listened to textually ambiguous sentences, which could be understood with prosodic cues, such as syllable length and pause length. Sentences were uttered in voices similar to the participant's own voice and in voices dissimilar to their own voice. The participants then identified which of four pictures the speaker was referring to. Both the eye movement and response time of the participants were recorded. Eye tracking and response time results both showed that participants understood the textually ambiguous sentences faster when listening to voices similar to their own. The results also suggest that tiny acoustic features, which do not contain verbal meaning can influence the processing of verbal information.

/pdf/impact-of-acoustic-similarity-on-efficiency-of-verbal-3ydydbrdb4.pdf

Kazuya Takeda

Papers

Recognition of continuous speech segments of monophone units using support vector machines.

Smart Mobile In-Vehicle Systems

Direction of arrival estimation based on nonlinear microphone array

Maximum a posterior probability and cumulative distribution function equalization methods for speech spectral estimation with application in noise suppression filtering

Impact of acoustic similarity on efficiency of verbal information transmission via subtle prosodic cues