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.

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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.

5. Probabilistic driver modeling Characterizing human behavior for semiautonomous vehicles

Interactive systems for in-vehicle applications have as their central goal the primary need to improve driver safety while allowing drivers effective control of vehicle functions, access to on-board or remote information, or safe hands-free human communications. Human-Computer interaction for in-vehicle systems requires effective audio capture, tracking of who is speaking, environmental noise suppression, and robust processing for applications such as route navigation, hands-free mobile communications, and human-to-human communications for hearing impaired subjects. In this chapter, we discuss safety with application for two interactive speech processing frameworks for in-vehicle systems. First, we consider integrating audio-visual processing for detecting the primary speech for a driver using a route navigation system. Integrating both visual and audio content allows us to reject unintended speech to be submitted for speech recognition within the route dialog system. Second, we consider a combined multi-channel array processing scheme based on a combined fixed and adaptive array processing scheme (CFA-BF) with a spectral constrained iterative Auto-LSP and auditory masked GMMSE-AMT-ERB processing for speech enhancement. The combined scheme takes advantage of the strengths offered by array processing methods in noisy environments, as well as speed and efficiency for single channel methods. We evaluate the audio-visual localization scheme for route navigation dialogs and show improved speech accuracy by up to 40% using the CIAIR in-vehicle data corpus from Nagoya, Japan. For the combined array processing and speech enhancement methods, we demonstrate consistent levels of noise suppression and voice communication quality improvement using a subset of the TIMIT corpus with four real noise sources, with an overall average 26dB increase in SegSNR from the original degraded audio corpus.

Speaker Source Localization Using Audio-Visual Data and Array Processing Based Speech Enhancement for In-Vehicle Environments

In order to improve the automated retrieval of similar songs, we need to develop an estimation method which can measure their subjective similarity. In this study, we assume that subjective similarity of songs is determined by both the acoustical similarity of the songs and the individuality of the listener. We focus mainly on the individuality of listeners, and use knowledge about this individuality to develop a subjective similarity estimation model. The results of our previous study suggest that the likelihood of someone judging two songs (a musical pair) as “similar” is influenced by the individual characteristics (individuality) of the listener. In this paper we refer to the likelihood of judging songs to be similar as the “tolerance” of the listener, and propose a model of subjective similarity evaluation which takes individual tolerance into account. In our experiment, we estimate listeners' tolerance using subjective musical similarity evaluation data. We also conduct an experiment using a much smaller amount of similarity evaluation data to estimate tolerance, as this would be desirable for practical applications.

Modeling subjective evaluation of music similarity using tolerance

Retrospective analysis of Odontogenic Sinusitis : 30 case series : Hiroki Kiri1), Masaki Hayama2, 3), Yohei Maeda2), Takashi Shikina2, 4), Chisako Masumura5), Suzuyo Okazaki6), Mika Okuno6), Kazuya Takeda2), Takeshi Tsuda2) and Hidenori Inohara2). 1)Department of Otorhinolaryngology, Osaka Police Hospital, 2)Department of Otorhinolaryngology-Head and Neck Surgery, Osaka University Graduate School of Medicine, 3)Department of Otorhinolaryngology, Yao Municipal Hospital, 4)Department of Otorhinolaryngology, Ikeda Municipal Hospital, 5)Department of Otorhinolaryngology, Suita Municipal Hospital, 6)Department of Otorhinolaryngology, Osaka City General Hospital

Retrospective analysis of Odontogenic Sinusitis: 30 case series

We assume that there is a correlation between an utterance and a corresponding gaze object, and propose a new paradigm of multi-modal end-to-end speech recognition using multimodal information, namely, utterances and corresponding gaze points. In our method, the system extracts acoustic features and corresponding images around gaze points, and inputs the information into the proposed attention-based multiple encoder-decoder networks. This makes it possible to integrate the two different modalities, and the performance of speech recognition is improved. To evaluate the proposed method, we prepared a simulation task of power-line control operations, and built a corpus that contains utterances and corresponding gaze points in the operations. We conducted an experimental evaluation using this corpus, and the results showed the reduction in the CER, suggesting the effectiveness of the proposed method in which acoustic features and gaze information are integrated.

Kazuya Takeda

Papers

5. Probabilistic driver modeling Characterizing human behavior for semiautonomous vehicles

Speaker Source Localization Using Audio-Visual Data and Array Processing Based Speech Enhancement for In-Vehicle Environments

Modeling subjective evaluation of music similarity using tolerance

Retrospective analysis of Odontogenic Sinusitis: 30 case series

Attention-Based Speech Recognition Using Gaze Information