Objective In recent years, there has been a marked increase in communication technologies and computer interfaces that operate within the audio-visual speech domain, (e.g. video-telephony, synthesised avatars, etc). Faithful synchrony between the visual and acoustic speech elements of such technologies is of great importance in ensuring that they are perceived by end-users as operating at high and optimal quality levels. The effect of intermodal asynchrony on user-perceived quality is typically assessed using subjective evaluation techniques. A system for automatically assessing asynchrony levels, and predicting quality degradation on that basis, would therefore be both desirable and useful, and will have direct application to techniques for automatic synchrony adjustment.The proposed project will examine audio-visual speech as both spoken naturally by humans and as artificially synthesised by machines, and will employ subjective assessment techniques and machine learning in a combined iterative semi-automatic strategy for producing a Quality Prediction Model. Different levels of intermodal asynchrony will first be assessed by human subjects, who will be required to score the effect of the asynchrony levels on perceived speech quality using standardisedtechniques that will be modified for use with multimodal speech. Asynchrony patterns and their corresponding subjective assessment scores will be automatically learned by machines, resulting in an initial Quality Prediction Model. The initial model will be tested using data that will be simultaneously assessed by humans, using the subjective assessment techniques, above. Theoutput from the prediction model will be directly compared with the subjective scores, providing an initial evaluation of the model's performance. The model will be adjusted on this basis, and re-trained using new data. The process of re-train, re-test, re-score, will be repeated iteratively, leading to a more robust quality prediction model. Fields of science engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networkshumanitieslanguages and literaturelinguisticsphoneticsnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Topic(s) FP7-PEOPLE-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development" Call for proposal FP7-PEOPLE-2010-IEF See other projects for this call Funding Scheme MC-IEF - Intra-European Fellowships (IEF) Coordinator TECHNISCHE UNIVERSITAT BERLIN Address Strasse des 17 juni 135 10623 Berlin Germany See on map Region Berlin Berlin Berlin Activity type Higher or Secondary Education Establishments Administrative Contact Simone Ludwig (Ms.) Links Contact the organisation Opens in new window Website Opens in new window EU contribution No data
