[Show abstract][Hide abstract] ABSTRACT: Expression of emotional state is considered to be a core facet of an individual's emotional competence. Emotional processing in BN has not been often studied and has not been considered from a broad perspective. This study aimed at examining the implicit and explicit emotional expression in BN patients, in the acute state and after recovery. Sixty-three female participants were included: 22 BN, 22 recovered BN (R-BN), and 19 healthy controls (HC). The clinical cases were drawn from consecutive admissions and diagnosed according to DSM-IV-TR diagnostic criteria. Self reported (explicit) emotional expression was measured with State-Trait Anger Expression Inventory-2, State-Trait Anxiety Inventory, and Symptom Check List-90 items-Revised. Emotional facial expression (implicit) was recorded by means of an integrated camera (by detecting Facial Feature Tracking), during a 20 minutes therapeutic video game. In the acute illness explicit emotional expression [anxiety (p<0.001) and anger (p<0.05)] was increased. In the recovered group this was decreased to an intermediate level between the acute illness and healthy controls [anxiety (p<0.001) and anger (p<0.05)]. In the implicit measurement of emotional expression patients with acute BN expressed more joy (p<0.001) and less anger (p<0.001) than both healthy controls and those in the recovered group. These findings suggest that there are differences in the implicit and explicit emotional processing in BN, which is significantly reduced after recovery, suggesting an improvement in emotional regulation.
PLoS ONE 07/2014; 9(7):e101639. DOI:10.1371/journal.pone.0101639 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Monitoring of animal communities is necessary to assess the conservation status of threatened species and to implement efficient conservation measures. However, classical observer-based survey techniques are expensive and time-consuming. Automated acoustic monitoring provides a solution for monitoring sound-emitting animals, such as mammals, birds, amphibians, and insects. Several Autonomous Recording Units (ARUs) can be simultaneously operated in 24/7 modus.
24th International Bioacoustics Congress (IBAC), Pirenopolis, Brazil; 09/2013
[Show abstract][Hide abstract] ABSTRACT: We report on the development of an automated acoustic bird recognizer with improved noise robustness, which is part of a long-term project, aiming at the establishment of an automated biodiversity monitoring system at the Hymettus Mountain near Athens, Greece. In particular, a typical audio processing strategy, which has been proved quite successful in various audio recognition applications, was amended with a simple and effective mechanism for integration of temporal contextual information in the decision-making process. In the present implementation, we consider integration of temporal contextual information by joint post-processing of the recognition results for a number of preceding and subsequent audio frames. In order to evaluate the usefulness of the proposed scheme on the task of acoustic bird recognition, we experimented with six widely used classifiers and a set of real-field audio recordings for seven bird species commonly present at the Hymettus Mountain. The highest achieved recognition accuracy obtained on the real-field data was approximately 93%, while experiments with additive noise showed significant robustness in low signal-to-noise ratio setups. In all cases, the integration of temporal contextual information was found to improve the overall accuracy of the recognizer.
International Journal of Intelligent Systems Technologies and Applications 07/2013; 5(7):9-15. DOI:10.5815/ijisa.2013.07.02
[Show abstract][Hide abstract] ABSTRACT: The MoveOn speech and noise database was purposely designed and implemented in support of research on spoken dialogue interaction in a motorcycle environment. The distinctiveness of the MoveOn database results from the requirements of the application domain—an information support and operational command and control system for the two-wheel police force—and also from the specifics of the adverse open-air acoustic environment. In this article, we first outline the target application, motivating the database design and purpose, and then report on the implementation details. The main challenges related to the choice of equipment, the organization of recording sessions, and some difficulties that were experienced during this effort, are discussed. We offer a detailed account of the database statistics, the suggested data splits in subsets, and discuss results from automatic speech recognition experiments which illustrate the degree of complexity of the operational environment.
Language Resources and Evaluation 06/2013; 47(2). DOI:10.1007/s10579-013-9222-7 · 0.52 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The performance of recent dereverberation methods for reverberant speech preprocessing prior to Automatic Speech Recognition (ASR) is compared for an extensive range of room and source-receiver configurations. It is shown that room acoustic parameters such as the clarity (C50) and the definition (D50) correlate well with the ASR results. When available, such room acoustic parameters can provide insight into reverberant speech ASR performance and potential improvement via dereverberation preprocessing. It is also shown that the application of a recent dereverberation method based on perceptual modelling can be used in the above context and achieve significant Phone Recognition (PR) improvement, especially under highly reverberant conditions.
[Show abstract][Hide abstract] ABSTRACT: We report on a recent progress with the development of an automated bioacoustic bird recognizer, which is part of a long-term project , aiming at the establishment of an automated biodiversity monitoring system at the Hymettus Mountain near Athens. In particular, employing a classical audio processing strategy, which has been proved quite successful in various audio recognition applications, we evaluate the appropriateness of six classifiers on the bird species recognition task. In the experimental evaluation of the acoustic bird recognizer, we made use of real-field audio recordings of two bird species, which are known to be present at the Hymettus Mountain. Encouraging recognition accuracy was obtained on the real-field data, and further experiments with additive noise demonstrated significant noise robustness in low SNR conditions.
IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI), 7-9 November 2012, Athens, Greece; 11/2012
[Show abstract][Hide abstract] ABSTRACT: We describe a novel design, implementation and evaluation of a speech interface, as part of a platform for the development of serious games. The speech interface consists of the speech recognition component and the emotion recognition from speech component. The speech interface relies on a platform designed and implemented to support the development of serious games, which supports cognitive-based treatment of patients with mental disorders. The implementation of the speech interface is based on the Olympus/RavenClaw framework. This framework has been extended for the needs of the specific serious games and the respective application domain, by integrating new components, such as emotion recognition from speech. The evaluation of the speech interface utilized purposely collected domain-specific dataset. The speech recognition experiments show that emotional speech moderately affects the performance of the speech interface. Furthermore, the emotion detectors demonstrated satisfying performance for the emotion states of interest, Anger and Boredom, and contributed towards successful modelling of the patient’s emotion status. The performance achieved for speech recognition and for the detection of the emotional states of interest was satisfactory. Recent evaluation of the serious games showed that the patients started to show new coping styles with negative emotions in normal stress life situations.
Expert Systems with Applications 09/2012; 39(12):11072–11079. DOI:10.1016/j.eswa.2012.03.067 · 1.97 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper gives an overview of the assessment and evaluation methods which have been used to determine the quality of the INSPIRE smart home system. The system allows different home appliances to be controlled via speech, and consists of speech and speaker recognition, speech understanding, dialogue management, and speech output components. The performance of these components is first assessed individually, and then the entire system is evaluated in an interaction experiment with test users. Initial results of the assessment and evaluation are given, in particular with respect to the transmission channel impact on speech and speaker recognition, and the assessment of speech output for different system metaphors.
[Show abstract][Hide abstract] ABSTRACT: We propose a two-stage phone duration modelling scheme, which can be applied for the improvement of prosody modelling in speech synthesis systems. This scheme builds on a number of independent feature constructors (FCs) employed in the first stage, and a phone duration model (PDM) which operates on an extended feature vector in the second stage. The feature vector, which acts as input to the first stage, consists of numerical and non-numerical linguistic features extracted from text. The extended feature vector is obtained by appending the phone duration predictions estimated by the FCs to the initial feature vector. Experiments on the American-English KED TIMIT and on the Modern Greek WCL-1 databases validated the advantage of the proposed two-stage scheme, improving prediction accuracy over the best individual predictor, and over a two-stage scheme which just fuses the first-stage outputs. Specifically, when compared to the best individual predictor, a relative reduction in the mean absolute error and the root mean square error of 3.9% and 3.9% on the KED TIMIT, and of 4.8% and 4.6% on the WCL-1 database, respectively, is observed.
[Show abstract][Hide abstract] ABSTRACT: We report on a research effort aiming at the development of an acoustic bird activity detector (ABAD), which plays an important role for automating the traditional biodiversity assessment studies -- presently performed by human experts. The proposed on-line ABAD is considered an integral part of an automated system for acoustic identification of bird species, which is currently under development. In particular, taking advantage of real-field recordings collected at the Hymettus Mountain near Athens, we investigate the applicability of various machine learning techniques for the needs of our ABAD, which is intended to run on a mobile device. Performance is reported in terms of recogni-tion accuracy on audio frame level, due to the restrictions imposed by the requirement of run-time decision making with limited memory and energy resources. We report recognition accuracy of approximately 86% on a frame level, which is quite promising and encourages further research efforts in that direction.
Artificial Intelligence: Theories and Applications, 1 edited by I. Maglogiannis, V. Plagianakos, I. Vlahavas, 05/2012: chapter 24: pages 190-197; Springer-Verlag Berlin Heidelberg., ISBN: 978-3-642-30447-7
[Show abstract][Hide abstract] ABSTRACT: Vehicle detection based on on-board mounted cameras is an integral component of many driver assistance systems aiming at alerting the driver about impending collisions. In this paper an automated algorithm for detection of preceding vehicles is proposed, based on the detection of rear vehicle lights. Unlike many systems which make use of static threshold boundaries for the red color segmentation of rear lights, our method combines color and radial symmetry cues while the threshold is dynamically adapted. The extracted candidate rear lights are morphologically paired in order to define possible areas where vehicles are present. The verification of vehicle presence is then carried out through axial symmetry check. Experimental results that demonstrate the system's high detection rates and robustness even in adverse illumination and weather conditions are finally presented.
International Conference on Systems, Signals and Image Processing (IWSSIP 2012); 04/2012
[Show abstract][Hide abstract] ABSTRACT: During the previous years, the field of emotional content analysis of speech signals has been gaining a lot of attention and several frameworks have been constructed by different researchers for recognition of human emotions in spoken utterances. This paper describes a series of exhaustive experiments which demonstrate the feasibility of recognizing human emotional states via integrating low level descriptors. Our aim is to investigate three different methodologies for integrating subsequent feature values. More specifically we used the following methods: a) short-term statistics, b) spectral moments and c) autoregressive models. Additionally we employed a newly introduced group of parameters which is based on the wavelet decomposition. These are compared with a baseline set comprised of descriptors which are usually used for the specific task. Subsequently we experimented on fusing these sets on the feature and log-likelihood levels. The classification step is based on hidden Markov models while several algorithms which can handle redundant information were used during fusion. We report results on the well-known and freely available database BERLIN using data of six emotional states. Our experiments show the importance of including information which is captured by the set based on multiresolution analysis and the efficacy of merging subsequent feature values.
[Show abstract][Hide abstract] ABSTRACT: In this paper we attempt to face common problems of handwritten documents such as nonparallel text lines in a page, hill and dale writing, slanted and connected characters. Towards this end an integrated system for document image preprocessing is presented. This system consists of the following modules: skew angle estimation and correction, line and word segmentation, slope and slant correction. The skew angle correction, slope correction and slant removing algorithms are based on a novel method that is a combination of the projection profile technique and the Wigner–Ville distribution. Furthermore, the skew angle correction algorithm can cope with pages whose text line skew angles vary, and handle them by areas. Our system can be used as a preprocessing stage to any handwriting character recognition or segmentation system as well as to any writer identification system. It was tested in a wide variety of handwritten document images of unconstrained English and Modern Greek text from about 100 writers. Additionally, combinations of the above algorithms have been used in the framework of the ACCeSS system (European project LE-1 1802, aiming at the automatic processing of application forms of insurance companies) as well as in the processing of GRUHD and IAM-B databases for automating the procedure of extracting data.
International Journal of Pattern Recognition and Artificial Intelligence 11/2011; 17(04). DOI:10.1142/S0218001403002538 · 0.56 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper deals with the problems stemming from the parsing of long sentences in quasi free word order languages. Due to the word order freedom of a large category of languages including Greek and the limitations of rule-based grammar parsers in parsing unrestricted texts of such languages, we propose a flexible and effective method for parsing long sentences of such languages that combines heuristic information and pattern-matching techniques in early processing levels. This method is deeply characterized by its simplicity and robustness. Although it has been developed and tested for the Greek language, its theoretical background, implementation algorithm and results are language independent and can be of considerable value for many practical natural language processing (NLP) applications involving parsing of unrestricted texts.
International Journal of Artificial Intelligence Tools 11/2011; 04(03). DOI:10.1142/S0218213095000152 · 0.32 Impact Factor