Charalampos Dimoulas

Investigation of broadcast-audio semantic analysis scenarios employing radio-programme-adaptive pattern classification

The present paper focuses on the investigation of various audio pattern classifiers in broadcast-audio semantic analysis, using radio-programme-adaptive classification strategies with supervised training. Multiple neural network topologies and training configurations are evaluated and compared in combination with feature-extraction, ranking and feature-selection procedures. Different pattern classification taxonomies are implemented, using programme-adapted multi-class definitions and hierarchical schemes. Hierarchical and hybrid classification taxonomies are deployed in speech analysis tasks, facilitating efficient speaker recognition/identification, speech/music discrimination, and generally speech/non-speech detection-segmentation. Exhaustive qualitative and quantitative evaluation is conducted, including indicative comparison with non-neural approaches. Hierarchical approaches offer classification-similarities for easy adaptation to generic radio-broadcast semantic analysis tasks. The proposed strategy exhibits increased efficiency in radio-programme content segmentation and classification, which is one of the most demanding audio semantics tasks. This strategy can be easily adapted in broader audio detection and classification problems, including additional real-world speech-communication demanding scenarios.

Novel wavelet domain Wiener filtering de-noising techniques: Application to bowel sounds captured by means of abdominal surface vibrations

Abstract This work focuses on the design and evaluation of efficient and accurate de-noising algorithms that combine robust signal enhancement and minimum signal distortion. The proposed method introduces novel, frequency depended, parametric, Wiener filtering techniques that involve Discrete Wavelet Transform and Wavelet Packets. Implementations of various decomposition schemes, different mother wavelets and various thresholding options were tested, while perceptual criteria were also taken into account. The introduced de-noising approach has been extensively tested on human bowel sounds, captured by means of abdominal surface vibration recordings, in order to be further utilized as a diagnostic tool. Qualitative and quantitative analysis of the methods performance, when applied to various types of recorded and synthetic sounds, revealed that the new approach works excellent with favourable results.

Joint wavelet video denoising and motion activity detection in multimodal human activity analysis: application to video-assisted bioacoustic/psychophysiological monitoring

The current work focuses on the design and implementation of an indoor surveillance application for long-term automated analysis of human activity, in a video-assisted biomedical monitoring system. Video processing is necessary to overcome noise-related problems, caused by suboptimal video capturing conditions, due to poor lighting or even complete darkness during overnight recordings. Modified wavelet-domain spatiotemporal Wiener filtering and motion-detection algorithms are employed to facilitate video enhancement, motion-activity-based indexing and summarization. Structural aspects for validation of the motion detection results are also used. The proposed system has been already deployed in monitoring of long-term abdominal sounds, for surveillance automation, motion-artefacts detection and connection with other psychophysiological parameters. However, it can be used to any video-assisted biomedical monitoring or other surveillance application with similar demands.

Live Broadcasting of High Definition Audiovisual Content Using HDTV over Broadband IP Networks

The current paper focuses on validating an implementation of a state-of-the art audiovisual (AV) technologies setup for live broadcasting of cultural shows, via broadband Internet. The main objective of the work was to study, configure, and setup dedicated audio-video equipment for the processes of capturing, processing, and transmission of extended resolution and high fidelity AV content in order to increase realism and achieve maximum audience sensation. Internet2 and GEANT broadband telecommunication networks were selected as the most applicable technology to deliver such traffic workloads. Validation procedures were conducted in combination with metric-based quality of service (QoS) and quality of experience (QoE) evaluation experiments for the quantification and the perceptual interpretation of the quality achieved during content reproduction. The implemented system was successfully applied in real-world applications, such as the transmission of cultural events from Thessaloniki Concert Hall throughout Greece as well as the reproduction of Philadelphia Orchestra performances (USA) via Internet2 and GEANT backbones.

Syncing Shared Multimedia through Audiovisual Bimodal Segmentation

This work emanates from the particularities residing in contemporary social media storytelling, where multiple users and publishing channels capture and share public events, experiences, and places. Multichannel presentation and visualization mechanisms are pursued along with novel audiovisual mixing (such as time-delay-compensation enhancement, perceptual mixing, quality-based content selection, linking to context-aware metadata, and propagating multimedia semantics), thus promoting multimodal social media editing, processing, and authoring. While the exploitation of multiple time-based media (audio and video) describing the same event may lead to significant content enhancement, difficulties regarding detection and temporal synchronization of multimedia events have to be overcome. In many cases, one can identify events based only on audio features, thus performing an initial cost-effective annotation of the multimedia content. This article introduces a new audio-driven approach for temporal alignment and management of shared audiovisual streams. The article presents the theoretical framework and demonstrates the methodology in real-world scenarios. This article is part of a special issue on social multimedia and storytelling.

Investigating quality of Experience and Learning (QoE & QoL) of audiovisual content broadcasting to learners over IP networks

This paper investigates the implementation and validation of different qualities for live broadcasting of courses over the Internet. The main aim of this work is to identify the adequate balance between the required bandwidth for live broadcasting and the Quality of Experience and Learning (QoE & QoL). The data used in this study was acquired from real-world learning scenarios.

Towards Intelligent Cross-Media Publishing: Media Practices and Technology Convergence Perspectives

This chapter investigates technological issues that have arisen in implementing cross-media publishing. Specifically the various content types (text, pictures, audio, video, etc.) that are included in cross-media publishing require different management and prerequisites with respect to the media publishing channels and the involved terminals at both ends, production and consumer. A modular content documentation, selection and management model is proposed for intelligent cross-media publishing automation, taking advantage of contemporary semantic multimodal interaction, sophisticated meta-data processing and Web 2.0/3.0 trends.

Emotional aspects in Quality of Experience and Learning (QoE & QoL) of audiovisual content in mediated learning

The present paper focuses on the implementation and validation of audiovisual content, quality evaluation approaches in mediated learning. The main aim of the work is to identify and describe the mechanisms that the attributes of source content (and its encoding properties) influence the learning process and the involved emotional aspects in terms of Quality of Experience and Learning (QoE & QoL) parameters. Subjective sentiment analysis tests are implemented along with QoE /QoL evaluation parameters and perceptually-adapted QoE metrics in real-world mediated learning scenarios. The obtained knowledge would be very helpful while preparing and designing audiovisual mediated tutoring and/or broadcasted distance learning courses, but also in many other fields associated with multimedia quality of experience and sentiment analysis.

Emotional descriptors and quality of experience (QoE) metrics in evaluating mediated learning

The present paper focuses on the extraction and evaluation of salient audiovisual features for the prediction of the encoding requirements in multimedia learning content. Decisions over audiovisual encoding are related to the perceived quality of experience (QoE), but also to the physical attributes of initial material (i.e. resolution, color range, motion activity, audio dynamic range, bandwidth, etc.). Recent research showed that such decisions can be really crucial during the production of audiovisual e-learning material, where poor encoding may lead to unaccepted QoE or even to the creation of negative emotional response. On the other hand, exaggerated high quality encoding may create increased bandwidth demands that are associated with annoying delays and irregular playback flow, resulting again in QoE degradation with similar emotional repulsion. Thus, there has to be a careful treatment with proper encoding balance during the production of both the networked distance learning and stand-alone audiovisual mediated resources. Such machine creativity strategies are investigated in the current work with the utilization of applicable audiovisual features, QoE metrics and emotional measures. The current work is part of a broader research, aiming at implementing intelligent models for optimal audiovisual production and encoding configuration, with respect to the source content attributes, the requested quality of experience (and learning) and the related emotional properties.

Embedding sound localization and spatial audio interaction through coincident microphones arrays

This paper discusses a methodology for embedding sound localization techniques for spatial audio interaction, aiming at matching the low computing capabilities of mobile and embedded systems. The main goal is to implement a sound localization system, using a microphone array that combines increased accuracy with compromised computational load and applicable layout size. In particular, four cardioid microphones are placed in a cross-shape arrangement, thus forming a planar coincident microphones array for horizontal direction of arrival estimation. The incorporation of two additional microphones at the perpendicular plane is also considered for 3D audio localization. The implemented system is evaluated through simulation experiments and real-world field measurements in comparison to B-Format based localization. Joint time frequency analysis is considered for improving the localization accuracy in pure SNR conditions. The utilization of multiple arrays is also discussed for 2D and 3D position estimations, as well as signal enhancement by means of time-delay compensation.