Depression State Assessment: Application for Detection of Depression by Speech

Gábor Kiss, Dávid Sztahó, Klára Vicsi


We present an application that detects depression by speech based on a speech feature extraction engine. The input of the application is a read speech sample and the output is predicted depression severity level (Beck Depression Inventory). The application analyses the speech sample and evaluates it using support vector regression (SVR). The developed system could assist general medical staff if no specialist is present to aid the diagnosis. If there is a suspicion that the speaker is suffering from depression, it is inevitable to seek special medical assistance. The application supports five native languages: English, French, German, Hungarian and Italian.


Cite as: Kiss, G., Sztahó, D., Vicsi, K. (2019) Depression State Assessment: Application for Detection of Depression by Speech. Proc. Interspeech 2019, 966-967.


@inproceedings{Kiss2019,
  author={Gábor Kiss and Dávid Sztahó and Klára Vicsi},
  title={{Depression State Assessment: Application for Detection of Depression by Speech}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={966--967}
}