Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Advances in formal Slavic linguistics 2016

Advances in Formal Slavic Linguistics 2016 initiates a new series of collective volumes on formal Slavic linguistics. It presents a selection of high quality papers authored by young and senior linguists from around the world and contains both empirically oriented work, underpinned by up-to-date experimental methods, as well as more theoretically grounded contributions. The volume covers all major linguistic areas, including morphosyntax, semantics, pragmatics, phonology, and their mutual interfaces. The particular topics discussed include argument structure, word order, case, agreement, tense, aspect, clausal left periphery, or segmental phonology. The topical breadth and analytical depth of the contributions reflect the vitality of the field of formal Slavic linguistics and prove its relevance to the global linguistic endeavour. Early versions of the papers included in this volume were presented at the conference on Formal Description of Slavic Languages 12 or at the satellite Works

On automatic emotion classification using acoustic features

In this thesis, we describe extensive experiments on the classification of emotions from speech using acoustic features. This area of research has important applications in human computer interaction. We have thoroughly reviewed the current literature and present our results on some of the contemporary emotional speech databases. The principal focus is on creating a large set of acoustic features, descriptive of different emotional states and finding methods for selecting a subset of best performing features by using feature selection methods. In this thesis we have looked at several traditional feature selection methods and propose a novel scheme which employs a preferential Borda voting strategy for ranking features. The comparative results show that our proposed scheme can strike a balance between accurate but computationally intensive wrapper methods and less accurate but computationally less intensive filter methods for feature selection. By using the selected features, several schemes for extending the binary classifiers to multiclass classification are tested. Some of these classifiers form serial combinations of binary classifiers while others use a hierarchical structure to perform this task. We describe a new hierarchical classification scheme, which we call Data-Driven Dimensional Emotion Classification (3DEC), whose decision hierarchy is based on non-metric multidimensional scaling (NMDS) of the data. This method of creating a hierarchical structure for the classification of emotion classes gives significant improvements over other methods tested. The NMDS representation of emotional speech data can be interpreted in terms of the well-known valence-arousal model of emotion. We find that this model does not givea particularly good fit to the data: although the arousal dimension can be identified easily, valence is not well represented in the transformed data. From the recognitionresults on these two dimensions, we conclude that valence and arousal dimensions are not orthogonal to each other. In the last part of this thesis, we deal with the very difficult but important topic of improving the generalisation capabilities of speech emotion recognition (SER) systems over different speakers and recording environments. This topic has been generally overlooked in the current research in this area. First we try the traditional methods used in automatic speech recognition (ASR) systems for improving the generalisation of SER in intra– and inter–database emotion classification. These traditional methods do improve the average accuracy of the emotion classifier. In this thesis, we identify these differences in the training and test data, due to speakers and acoustic environments, as a covariate shift. This shift is minimised by using importance weighting algorithms from the emerging field of transfer learning to guide the learning algorithm towards that training data which gives better representation of testing data. Our results show that importance weighting algorithms can be used to minimise the differences between the training and testing data. We also test the effectiveness of importance weighting algorithms on inter–database and cross-lingual emotion recognition. From these results, we draw conclusions about the universal nature of emotions across different languages

Advances in formal Slavic linguistics 2016

Advances in Formal Slavic Linguistics 2016 initiates a new series of collective volumes on formal Slavic linguistics. It presents a selection of high quality papers authored by young and senior linguists from around the world and contains both empirically oriented work, underpinned by up-to-date experimental methods, as well as more theoretically grounded contributions. The volume covers all major linguistic areas, including morphosyntax, semantics, pragmatics, phonology, and their mutual interfaces. The particular topics discussed include argument structure, word order, case, agreement, tense, aspect, clausal left periphery, or segmental phonology. The topical breadth and analytical depth of the contributions reflect the vitality of the field of formal Slavic linguistics and prove its relevance to the global linguistic endeavour. Early versions of the papers included in this volume were presented at the conference on Formal Description of Slavic Languages 12 or at the satellite Workshop on Formal and Experimental Semantics and Pragmatics, which were held on December 7-10, 2016 in Berlin

Speech Recognition

Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes

CLARIN

The book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium