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.

An integrated audio-visual viewer for a large scale multipoint cameras and microphones

We describe a new real-time isolated word recognizer with improved user interface. The recognizer is designed for an Extension Number Guidance System which looks up and announces an extension number by telephone dialogue with users. To deal with telephone quality speech input which include noise and distortion during transmission over the telephone network, we developed feature extraction and a word detection algorithm. These techniques use wide band-pass filter outputs which are generally employed to decide whether speech is voiced or unvoiced. To achieve a friendly interface, the system can accept user input at any time by using an echo canceler and the new word detection algorithm. Finally, the recognizer is evaluated using a large telephone voice database consisting of more than 500 speakers.

https://www.jstage.jst.go.jp/article/ast1980/15/2/15_2_87/_pdf

A real-time isolated word recognizer for telephone input.

We propose a flexible and robust SNR estimation method for the real conditions, when neither clean reference signal nor speech activity is available. This method is based on Gaussian mixture modeling on the log-power domain of the noisy speech and use the estimated subspace distribution parameters to derive the SNR measures. The experimental results show better performance in estimating both the segmental and global SNR compared to the conventional method based on voice activity detection (VAD). The second application presented in this work is local noise power estimation, where the same model is applied to each frequency bin. Furthermore, an empirical MAP solution using second order statistics is applied to estimate the local noise powers in order to implement a Wiener filtering system. The evaluation experiments show the improvements of the proposed speech enhancement method in both segmental SNR and automatic speech recognition (ASR) performance.

SNR and local noise power estimations based on Gaussian mixture modeling on the log-power domain

PURPOSE:To suppress misrecognition by performing switch operation according to a word prediction result, connecting word collating process parts and grammatical state processing parts without any operator's intervention, and employing only a sentence generated with only predicted words as a recognition candidate. CONSTITUTION:The device consists of an acoustic analytic part 1 which converts an input speech into a feature parameter sequence at proper time intervals, word matching process parts 2-6 which collates the analysis result of the analytic part with previously registered words, grammatical state process parts 7-10 which receive cumulative likelihood of time from the collating process parts and hold words granting the most excellent cumulative collation results, and a back track process part 11 which determines and outputs a word sequence as a recognition result and is provided with a word prediction part 13 which generates a predicted word by using a word relation table; and the device is further provided with predicted word passage switches 14-16 which send only the sentence consisting of only predicted words to the grammatical state process parts, the switch operation is performed according to the word prediction result, so that only the sentence consisting of only the predicted words is employed as the recognition candidate.

Continuous speech recognizing method and device using the same

We address issues for improving hands-free speech enhancement and speech recognition performance in different car environments using a single distant microphone. This paper describes a new single-channel in-car speech enhancement method that estimates the log spectra of speech at a close-talking microphone based on the nonlinear regression of the log spectra of noisy signal captured by a distant microphone and the estimated noise. The proposed method provides significant overall quality improvements in our subjective evaluation on the regression-enhanced speech, and performed best in most objective measures. Based on our isolated word recognition experiments conducted under 15 real car environments, the proposed adaptive nonlinear regression approach shows an advantage in average relative word error rate (WER) reductions of 50.8% and 13.1%, respectively, compared to original noisy speech and ETSI advanced front-end (ETSI ES 202 050).

Kazuya Takeda

Papers

An integrated audio-visual viewer for a large scale multipoint cameras and microphones

A real-time isolated word recognizer for telephone input.

SNR and local noise power estimations based on Gaussian mixture modeling on the log-power domain

Continuous speech recognizing method and device using the same

Single-Channel Multiple Regression for In-Car Speech Enhancement