[{"id":343044,"last_updated":"2023-11-06 19:31:25","id_people":472155,"institutes":["ILC"],"type":"conference_article","type_order":5,"type_people":"conferenceObject","title":"Analyzing the Interaction between the Reader's Voice and the Linguistic Structure of the Text: a Preliminary Study","year":2021,"authors_people":"Iavarone B., Morelli M. S., Brunato D., Ghiasi S., Scilingo E. P., Vanello N., Dell'Orletta F., Greco A.","authors_cnr":["Dell'Orletta, Felice","Brunato, Dominique Pierina"],"authors_cnr_id":["14329","21125"],"authors_cnr_institute":[""],"authors":["Iavarone, B.","Morelli, M. S.","Brunato, D.","Ghiasi, S.","Scilingo, E. P.","Vanello, N.","Dell'Orletta, F.","Greco, A."],"abstract":"In this study, we present a preliminary analysis of the relationship between the linguistic profile of a text and the voice properties of the reader aiming to improve the speech-based emotion recognition systems. To this aim, we recorded the speech signals from a group of 32 healthy volunteers reading aloud neutral and affective texts and used the BioVoice toolbox to compute some of the main speech features. The selected texts were analyzed to quantify their lexical, morpho-syntactic, and syntactic content. Correlation and Support Vector Regressor analyses between linguistic and speech features have shown a significant modulation of some voice acoustic properties performed by the linguistic structure of the text. Particularly, a significant effect was shown on some specific speech features often used for the assessment of human emotional state (e.g., F0). This suggests that the lexical, morpho-syntactic, and syntactic properties could play an important role in the emotional dynamics of a person.","keywords":["Natural Language Processing","Speech analysis","linguistic profile"],"pages":"","url":"https:\/\/publications.cnr.it\/doc\/472155","volume":"","doi":"10.36253\/978-88-5518-449-6","editors_people":"","editors":[""],"published":"Proceedings of 12th INTERNATIONAL WORKSHOP \"MODELS AND ANALYSIS OF VOCAL EMISSIONS FOR BIOMEDICAL APPLICATIONS\"","publisher":"","issn":"","isbn":"978-88-5518-448-9","conference_name":"12th INTERNATIONAL WORKSHOP \"MODELS AND ANALYSIS OF VOCAL EMISSIONS FOR BIOMEDICAL APPLICATIONS\"","conference_place":"Firenze, Italia","conference_date":"14-16\/12\/2021"},{"id":132308,"last_updated":"2023-11-06 19:32:26","id_people":391619,"institutes":["ILC"],"type":"conference_article","type_order":5,"type_people":"conferenceObject","title":"Is this sentence difficult? Do you agree?","year":2018,"authors_people":"Brunato D., De Mattei L., Dell'Orletta F., Iavarone B., Venturi G.","authors_cnr":["Brunato, Dominique Pierina","Dell'Orletta, Felice","Venturi, Giulia"],"authors_cnr_id":["14329","17692"],"authors_cnr_institute":[""],"authors":["Brunato, D.","De Mattei, L.","Dell'Orletta, F.","Iavarone, B.","Venturi, G."],"abstract":"In this paper, we present a crowdsourcing-based approach to model the human perception of sentence complexity. We collect a large corpus of sentences rated with judgments of complexity for two typologically-different languages, Italian and English. We test our approach in two experimental scenarios aimed to investigate the contribution of a wide set of lexical, morpho-syntactic and syntactic phenomena in predicting i) the degree of agreement among annotators independently from the assigned judgment and ii) the perception of sentence complexity.","keywords":["Linguistic complexity","Crowdsourcing","Human perception"],"pages":"1-10","url":"https:\/\/www.aclweb.org\/anthology\/D18-1289\/","volume":"","doi":"10.18653\/v1\/D18-1289","editors_people":"","editors":[""],"published":"","publisher":"Association for Computational Linguistics (Stroudsburg, USA)","issn":"","isbn":"978-1-948087-84-1","conference_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","conference_place":"Brussels","conference_date":"31\/10\/2018-04\/11\/2018"}]