Szczegóły publikacji
Opis bibliograficzny
Leveraging text and speech processing for suicide risk classification in Chinese adolescents / Justyna Krzywdziak, Bartłomiej Eljasiak, Joanna Stępień, Michał Świątek, Agnieszka Pruszek // W: Interspeech 2025 [Dokument elektroniczny] : 17–21 August 2025, Rotterdam, The Netherlands. — Wersja do Windows. — Dane tekstowe. — [France : ISCA], [2025]. — ( Interspeech : proceedings of the ... Annual Conference of the International Speech Communication Association ; ISSN 2958-1796 ). — S. 394–398. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 398, Abstr. — J. Krzywdziak - afiliacja: Samsung R&D Institute Poland
Autorzy (5)
- Krzywdziak Justyna
- Eljasiak Bartłomiej
- Stępień Joanna
- Świątek Michał
- Pruszek Agnieszka
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 165876 |
|---|---|
| Data dodania do BaDAP | 2026-03-06 |
| Tekst źródłowy | URL |
| DOI | 10.21437/Interspeech.2025-2755 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | Interspeech 2025 |
| Czasopismo/seria | Interspeech |
Abstract
The increasing prevalence of depression among young people is a growing global concern. Early detection and intervention are crucial, making the development of effective diagnostic tools essential. This work explores the use of advanced text and speech processing techniques to classify suicide risk within the context of the SpeechWellness Challenge (SW1) and verifies if speech can be used as a non-invasive and readily available mental health indicator. The analysis incorporated both linguistic features and audio-based methods for spontaneous speech and passage reading. For text classification, Large Language Models like Qwen2.5 and BERT were evaluated. For audio-based prediction, state-of-the-art speech processing models, including Whisper, Wav2Vec2 and HuBERT were employed. Furthermore, a multimodal approach combining both vocal and textual features was investigated. The results obtained in this research ranked among the highest in the challenge.
