Scientific seminar: Artificial intelligence to identify depression from audio information

On Wednesday, May 29, at 14:00, as part of a series of scientific seminars at the Laboratory of Artificial Intelligence for Cognitive Sciences, Anna Kazachkova will hold the talk on topic: Artificial intelligence to identify depression from audio information.

Subject: Artificial intelligence to identify depression from audio information

Abstract.
Depression is a widespread psychiatric disorder, which can significantly deteriorate the quality of life. Automatic depression detection could be an accessible and reliable diagnostic tool, addressing the current issues in the mental disorders area. The purpose of this paper is to study how accurately depression can be predicted on a given dataset and what are the most sustainable models and data representations. The study focuses on problem formulations such as binary classification and abnormality detection. The exploited models included convolutional neural networks and the transformer, and they were either trained only on our dataset or employed in the form of pre-trained for the image classification instances. Additionally, a benchmark of classical machine learning algorithms for the Geneva Minimalistic Acoustic Parameter Set features was computed. In total, we derived the best average ROC-AUC value of 0.72 on the test, compared to the benchmark of 0.55. This best result was provided by fine-tuning InceptionV3 architecture under the one-plus-epsilon optimization algorithm.

The presentation will be delivered by: Anna Kazachkova(HSE MS student)

Supervisor: Shalileh Soroosh (Ph.D. in Computer Science, Laboratory Head)

The meeting will be held in a hybrid format. We meet in person at the address: Krivokolenny lane, 3, room 302 or online in Zoom.

To participate in the seminar, please register.

To order passes for external members of the seminar please contact laboratory manager Lobashova Alina: aalobashova@hse.ru or +7 (927) 407 21-84.