The Directional Dependence of the Lunar Cherenkov Technique for UHE Neutrino Detection

The LUNASKA (Lunar UHE Neutrino Astrophysics with the Square Kilometre Array) project is a theoretical and experimental project developing the lunar Cherenkov technique for the next generation of giant radio-telescope arrays. This contribution presents our simulation results on the directional dependence of the technique for UHE neutrino detection. In particular, these indicate that both the instantaneous sensitivities and time-integrated limits from lunar Cherenkov experiments such as those at Parkes, Goldstone, Kalyazin and ATCA are highly anisotropic. We study the regions of the sky which have not been probed by either these or other experiments, and present the expected sky coverage of future experiments with the SKA. Our results show how the sensitivity of Lunar Cherenkov observations to potential astrophysical sources of UHE particles may be maximised by choosing appropriate observations dates and antenna-beam pointing positions.Comment: 4 pages, 4 figures, presented at ARENA 2008, Rome, Ital

Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News

This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. T. Theodorou, I. Mpoas, A. Lazaridis, N. Fakotakis, 'Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News', International Journal on Artificial Intelligence Tools, Vol. 26 (2), April 2017, 1750005 (13 pages), DOI: 10.1142/S021821301750005. © The Author(s).In this paper we describe an automatic sound recognition scheme for radio broadcast news based on principal component clustering with respect to the discrimination ability of the principal components. Specifically, streams of broadcast news transmissions, labeled based on the audio event, are decomposed using a large set of audio descriptors and project into the principal component space. A data-driven algorithm clusters the relevance of the components. The component subspaces are used by sound type classifier. This methodology showed that the k-nearest neighbor and the artificial intelligent network provide good results. Also, this methodology showed that discarding unnecessary dimension works in favor on the outcome, as it hardly deteriorates the effectiveness of the algorithms.Peer reviewe

INSPIRE: Evaluation of a Smart-Home System for Infotainment Management and Device Control

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.Comment: 4 page

Explicit and implicit emotional expression in bulimia nervosa in the acute state and after recovery

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

Speech/music discrimination based on discrete wavelet transform

In this paper we present an effective approach which addresses the issue of speech/music discrimination. Our architecture focuses on the matter from the scope of improving the performance of a speech recognition system by excluding the processing of information which is not speech. Multiresolution analysis is applied to the input signal while the most significant statistical features are calculated over a predefined texture size. These characteristics are then modeled using a state of the art technique for probability density function estimation, Gaussian mixture models (GMM). A classification scheme consisting of a conventional maximum likelihood decision methodology constitutes the next step of our implementation. Despite the fact that our system is based solely on wavelet signal processing, it demonstrated very good performance achieving 91.8% recognition rate. © 2008 Springer-Verlag Berlin Heidelberg

A NEW METHOD OF AUTOMATIC SPEAKER RECOGNITION

THE THESIS PRESENTS A NEW METHOD FOR AN AUTOMATIC SPEAKER RECOGNITION SYSTEM, WHICH COULD BE FAVORABLY IMPLEMENTED FOR IDENTIFICATION AS WELL AS FOR VERIFICATION PURPOSES. THIS METHOD IS BASED ON A SUBSTANTIALLY REDUCED NUMBER OF ELEMENTS OF THE PATTERN VECTOR IN COMPARISON TO SIMILAR METHODS. THE ELEMENTS ARE FREQUENCIES OF THE FIRST THREE FORMANTS WHICH CORRESPOND TO CHARACTERISTIC PEAKS OF THE ENERGY-TIME TRAJECTORY OF THE SPEECH SIGNAL AND ARE EXTRACTED AUTOMATICALLY WITHOUT PREVIOUS WARPING OF THE SPEECH SIGNAL. THE SPEECH EVENTS ARE LOCATED TAKING INTO ACCOUNT THE DISTANCE BETWEEN ADJACENT EXTREMES AND THEIR ENERGIES. IT SHOULD BE NOTICED THAT THE UTTERANCE IS SPECIALLY CHOSEN TO PRESENT THE DISTINCTIVE EXTREMES (SPEECH EVENTS).ΣΤΗ ΔΙΑΤΡΙΒΗ ΠΑΡΟΥΣΙΑΖΕΤΑΙ ΜΙΑ ΝΕΑ ΜΕΘΟΔΟΣ ΑΥΤΟΜΑΤΗΣ ΑΝΑΓΝΩΡΙΣΕΩΣ ΟΜΙΛΗΤΗ (ΕΞΑΚΡΙΒΩΣΕΩΣ ΚΑΙ ΕΠΙΒΕΒΑΙΩΣΕΩΣ), ΠΟΥ ΒΑΣΙΖΕΤΑΙ ΣΕ ΕΙΔΙΚΑ ΕΠΙΛΕΓΜΕΝΟ ΚΕΙΜΕΝΟ ΟΜΙΛΙΑΣ. ΤΟ ΚΕΙΜΕΝΟ ΑΠΟΤΕΛΕΙΤΑΙ ΑΠΟ ΠΡΟΤΑΣΗ (# ΠΡΟΤΑΣΕΙΣ) ΣΤΗΝ ΟΠΟΙΑ ΕΝΑΛΛΑΣΣΟΝΤΑΙ ΗΧΗΡΟΙ ΚΑΙ ΑΦΩΝΟΙ ΦΘΟΓΓΟΙ. ΟΙ ΗΧΗΡΟΙ ΦΘΟΓΓΟΙ ΑΠΟΤΕΛΟΥΝ ΧΑΡΑΚΤΗΡΙΣΤΙΚΑ ΣΗΜΕΙΑ ΤΟΥ ΣΗΜΑΤΟΣ ΟΜΙΛΙΑΣ, ΑΠΟ ΤΑ ΟΠΟΙΑ ΕΞΑΓΟΝΤΑΙ ΟΙ 3 ΠΡΩΤΕΣ ΣΥΧΝΟΤΗΤΕΣ ΣΥΝΤΟΝΙΣΜΟΥ ΤΗΣ ΦΩΝΗΤΙΚΗΣ ΟΔΟΥ, ΠΟΥ ΧΡΗΣΙΜΟΠΟΙΟΥΝΤΑΙ ΩΣ ΠΑΡΑΜΕΤΡΟΙ ΑΝΑΓΝΩΡΙΣΕΩΣ. ΕΑΝ Κ ΕΙΝΑΙ ΟΙ ΗΧΗΡΟΙ ΦΘΟΓΓΟΙ ΤΟΥ ΚΕΙΜΕΝΟΥ, ΤΟ ΠΑΡΑΜΕΤΡΙΚΟ ΔΙΑΝΥΣΜΑ ΑΝΑΓΝΩΡΙΣΕΩΣ ΕΧΕΙ ΔΙΑΣΤΑΣΕΙΣ 3Κ. ΒΑΣΙΚΟ ΓΝΩΡΙΣΜΑ ΤΗΣ ΝΕΑΣ ΜΕΘΟΔΟΥ ΕΙΝΑΙ ΟΤΙ ΧΡΗΣΙΜΟΠΟΙΕΙ ΜΟΝΟ 3ΚΠΑΡΑΜΕΤΡΟΥΣ ΑΠΟ ΟΛΟΚΛΗΡΟ ΤΟ ΣΗΜΑ ΟΜΙΛΙΑΣ ΚΑΙ ΟΧΙ ΤΗΝ ΠΛΗΡΗ ΧΡΟΝΙΚΗ ΜΕΤΑΒΟΛΗ ΤΩΝ ΣΥΧΝΟΤΗΤΩΝ ΣΥΝΤΟΝΙΣΜΟΥ, ΟΠΩΣ ΑΝΑΛΟΓΕΣ ΜΕΘΟΔΟΙ. ΕΠΙΣΗΣ ΔΕΝ ΑΠΑΙΤΕΙ ΧΡΟΝΙΚΗ ΑΝΤΙΣΤΟΙΧΙΣΗ (TIME WARPING) ΤΩΝ ΣΗΜΑΤΩΝ ΑΝΑΦΟΡΑΣ ΚΑΙ ΔΟΚΙΜΗΣ. ΑΥΤΑ ΕΧΟΥΝ ΩΣ ΣΥΝΕΠΕΙΑ ΣΗΜΑΝΤΙΚΗ ΜΕΙΩΣΗ ΤΟΥ ΑΠΑΙΤΟΥΜΕΝΟΥ ΟΓΚΟΥ ΜΝΗΜΗΣ ΓΙΑ ΤΑ ΔΕΔΟΜΕΝΑ ΑΝΑΦΟΡΑΣ ΚΑΙ ΔΟΚΙΜΗΣ ΚΑΙ ΑΥΞΗΣΗ ΤΗΣ ΤΑΧΥΤΗΤΑΣ ΑΠΟΚΡΙΣΗΣ ΤΟΥ ΣΥΣΤΗΜΑΤΟΣ. Η ΝΕΑ ΜΕΘΟΔΟΣ ΧΡΗΣΙΜΟΠΟΙΕΙ ΠΑΡΑΛΛΗΛΑ ΜΕ ΓΝΩΣΤΟΥΣ ΑΛΓΟΡΙΘΜΟΥΣ, ΝΕΟΥΣ 'Η ΒΕΛΤΙΩΜΕΝΟΥΣ ΑΛΓΟΡΙΘΜΟΥΣ ΣΕ ΒΑΣΙΚΑ ΤΜΗΜΑΤΑ ΤΗΣ ΔΙΑΔΙΚΑΣΙΑΣ ΕΠΕΞΕΡΓΑΣΙΑΣ ΤΟΥ ΣΗΜΑΤΟΣ ΟΜΙΛΙΑΣ ΚΑΙ ΜΕΧΡΙ ΤΗ ΛΗΨΗ ΑΠΟΦΑΣΕΩΣ, ΟΠΩΣ ΕΙΝΑΙ Η ΑΝΙΧΝΕΥΣΗ ΤΩΝ ΑΚΡΩΝ ΤΟΥ ΚΕΙΜΕΝΟΥ ΣΤΟ ΣΗΜΑ ΟΜΙΛΙΑΣ, Η ΕΞΑΓΩΓΗ ΤΩΝ ΣΥΝΤΟΝΙΣΜΩΝ (FORMANTS), Η ΕΞΟΜΑΛΥΝΣΗ ΤΗΣ ΧΡΟΝΙΚΗΣ ΣΥΝΑΡΤΗΣΕΩΣ ΤΩΝ ΣΥΝΤΟΝΙΣΜΩΝ, Η ΑΥΤΟΜΑΤΗ ΤΕΜΑΧΙΟΠΟΙΗΣΗ ΤΟΥ ΣΗΜΑΤΟΣ, Ο ΠΡΟΣΔΙΟΡΙΣΜΟΣ ΤΟΥ ΚΑΤΩΦΛΙΟΥ ΑΠΟΦΑΣΗΣ ΚΑΙ Ο ΕΠΑΝΑΠΡΟΣΔΙΟΡΙΣΜΟΣ ΤΩΝ ΔΕΔΟΜΕΝΩΝ ΑΝΑΦΟΡΑΣ

Modeling the temporal evolution of acoustic parameters for speech emotion recognition

During recent 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: 1) short-term statistics, 2) spectral moments, and 3) 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. © 2010-2012 IEEE

Automatic Extraction of Semantic Relations from Specialized Corpora

In this paper we address the problem of discovering word semantic similarities via statistical processing of text corpora. We propose a knowledge-poor method that exploits the sentencial context of words for extracting similarity relations between them as well as semantic in nature word clusters. The approach aims at full portability across domains and languages and therefore is based on minimal resources