Romanian Journal of Information Science and Technology (ROMJIST)

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ROMJIST is a publication of Romanian Academy,
Section for Information Science and Technology

Editor – in – Chief:
Academician Dan Dascalu

Secretariate (office):
Adriana Neagu
Adress for correspondence: romjist@nano-link.net (after 1st of January, 2019)

Editing of the printed version: Mihaela Marian (Publishing House of the Romanian Academy, Bucharest)

Editing of the on-line version: Lucian Milea (University POLITEHNICA of Bucharest)

Sponsors:
• National Institute for R & D
in Microtechnologies
(IMT Bucharest), www.imt.ro
• Association for Generic
and Industrial Technologies (ASTEGI), www.astegi.ro

ROMJIST Volume 21, No. 4, 2018, pp. 460-474, Paper no. 613/2018
 

Eduard FRANȚI, Monica DASCĂLU, Ioan ISPAS, Ana Voichita TEBEANU, Zoltan ELTETO, Silvia BRANEA, Voichita DRAGOMIR
Decoding communication: a deep learning approach to voice-based intention detection

ABSTRACT: This paper presents an original method of intention detection that can open a new direction of research in voice-based affective computing. A deep learning approach was used to detect the consistency between real and expressed intentions of a speaker (or the inconsistency, that is related to deceiving – or manipulative – intention), as reflected in the voice. The labelling and triangulation of results implies a qualitative research method, critical discourse analysis, and require expert evaluation. The method was implemented in a software platform integrated with the neural network programming frame. The deep learning architecture selected is based on similar models used by the authors in affective computing applications. The experimental researched applied the proposed method for a famous historical case: US President Richard Nixon’s audio speeches from the ‘Watergate affair’. A labelled data base of 2758 files (2 seconds audio fragments) was generated, based on publicly available voice recordings of President Nixon. These files were used for training and tests and an accuracy of over accuracy of over 94% was obtained

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