The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences

Abstract

Objectives. The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. Methods. Following its development, presented with, the Athens Emotional States Inventory (AESI) proposes the design, recording and validation of an audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. The items of the AESI consist of sentences each having content indicative of the corresponding emotion. Emotional content was assessed through a survey of 40 young participants with a questionnaire following the Latin square design. The emotional sentences that were correctly identified by 85% of the participants were recorded in a soundproof room with microphones and cameras. A preliminary validation of AESI is performed through automatic emotion recognition experiments from speech. Results. The resulting database contains 696 recorded utterances in Greek language by 20 native speakers and has a total duration of approximately 28 min. Speech classification results yield accuracy up to 75.15% for automatically recognizing the emotions in AESI. Conclusions. These results indicate the usefulness of our approach for collecting emotional data with reliable content, balanced across classes and with reduced environmental variability.

Key words::

• expressed emotion
• questionnaires
• data collection
• factual databases
• automatic data processing

Acknowledgments

The authors would like to thank Professor Thomas Paparrigopoulos, psychiatrist, Dr. Golfo Liamaki, clinical psychologist, for their constructive comments in the early stage of the formation of this paper as well as Professor Athanassios Protopapas, cognitive scientist, for his valuable advice on the recording room and equipment setting. The authors would also like to thank Dr. Stelios Krasanakis, psychiatrist and drama therapist, for his critical help in formulating the AESI sentences. Finally, special thanks are due to Dr. Dimitrios Dimitriadis for his contribution on the classification experiments. P. Maragos' research work was supported in part by the project COGNIMUSE which is implemented under the ARISTEIA Action of the Operational Program Education and Lifelong Learning and is co-funded by the European Social Fund and Greek National Resources.

Statement of Interest

None to declare.