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.

A parametric conversion of speech individuality is proposed based on STRAIGHT speech representation. STRAIGHT speech analysis-synthesis can produce high quality speech for various kinds of transformations by using 1) pitch synchronous windowing, 2) time-frequency spectrum interpolating and 3) randomized all-pass filtering for shaping phase spectrum. In order to utilize the smoothness of STRAIGHT spectrum, speech conversion is accomplished by warping the frequency axis. The warping functions are trained for each class of the predetermined spectrum shape grouping. The evaluation test is performed to compare the proposed method and VQ prototype mapping or linear transformation of cepstrum vectors. As a measure of converted speech quality, the MOS score of 6 subjects is calculated and is found to be better than conventional methods by about 1.5 point without degrading the accuracy of speech individuality discrimination.

Speaker conversion through non-linear frequency warping of straight spectrum.

With the increased presence and recent advances of drive recorders, rich driving data that include video, vehicle acceleration signals, driver speech, GPS data, and several sensor signals can be continuously recorded and stored. These advances enable researchers to study driving behavior more extensively for traffic safety. However, increasing the variety and the amount of driving data complicates the simultaneous browsing of various data and finding desired data from large databases. In this study, we develop a browsing and retrieval system for driving data that provides a multi-modal data browser, query- and similarity-based retrieval functions, and a fast browsing function that skips redundant scenes. For sharing data with several users, this system can be used via networks from PCs or smartphones, This system uses a time-series active search, which has been successfully used for fast search of audio and video data, as its retrieval function algorithm. In a few seconds, this system can retrieve driving scenes that are similar to an input scene from 80,000 scenes. Retrieval performance was compared in various retrieval conditions by changing the codebook size of the vector quantization for the histogram features and a combination of driving signals. Experimental results showed that more than 97% retrieval performance was achieved for driving behaviors of left/right turns and curves using a combination of such complementary information as steering angles and lateral acceleration. We also compared the proposed method to a conventional image-based retrieval method using subjective similarity scores of driving scenes. Our proposed system retrieved similar scenes with about a 75% retrieval performance that was five points higher than a conventional image-based retrieval method. It is because image-based method is sensitive to changes of image in the area except in the region of interest for driving data retrieval. The fast browsing function also skipped scenes that could not be skipped by an image-based method.

A browsing and retrieval system for driving data

In this study, we focus on the classification of neutral and stressed speech based on a physical model. In order to represent the characteristics of the vocal folds and vocal tract during the process of speech production and to explore the physical parameters involved, we propose a method using the two-mass model. As feature parameters, we focus on stiffness parameters of the vocal folds, vocal tract length, and cross-sectional areas of the vocal tract. The stiffness parameters and the area of the entrance to the vocal tract are extracted from the two-mass model after we fit the model to real data using our proposed algorithm. These parameters are related to the velocity of glottal airflow and acoustic interaction between the vocal folds and the vocal tract and can precisely represent features of speech under stress because they are affected by the speaker’s psychological state during speech production. In our experiments, the physical features generated using the proposed approach are compared with traditionally used features, and the results demonstrate a clear improvement of up to 10% to 15% in average stress classification performance, which shows that our proposed method is more effective than conventional methods.

/pdf/classification-of-speech-under-stress-based-on-modeling-of-3e4zc6f5y8.pdf

Classification of speech under stress based on modeling of the vocal folds and vocal tract

A speech morphing algorithm based on progressive interpolation of spectral envelopes and source signals is proposed. The basic morphing scheme is; 1) determine the time correspondence for unit waveforms of original and target speech, 2) separate speech spectra into an envelope and a sound source, 3) obtain the frequency correspondence for spectral channels of original and target speech for each envelope, 4) interpolate both source signal and envelope, 5) construct a unit waveform, and 6) generate morphing speech by PSOLA. In the objective test, the proposed method can reduce the spectral distortion by 1.9 dB in comparison with the method based on progressive substitution of spectra, when it is used for interpolating two vowels in a real speech. The effectiveness of the method is also confirmed by a subjective test in which 89% (male to female) or 93% (female to male) subjects preferred the proposed method. © 1998 Scripta Technica, Electron Comm Jpn Pt 3, 82(3): 22–30, 1999

Kazuya Takeda

Papers

Speaker conversion through non-linear frequency warping of straight spectrum.

A browsing and retrieval system for driving data

Classification of speech under stress based on modeling of the vocal folds and vocal tract

Speech morphing by independent interpolation of a spectral envelope and source excitation

Advances for In-Vehicle and Mobile Systems