This study illustrates how variations in test and train set sizes impact performance in a controlled study.

Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. September 2022. DOI:10.21437/Interspeech.2022-10888.

Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. T Rutowski, A Harati, E Shriberg, Y Lu, P Chlebek ...

The first and larger corpus contains younger speakers. It is used to train an NLP model to predict depression. When testing on unseen speakers from the same age ...

2020. Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. T Rutowski, A Harati, E Shriberg, Y Lu, P ...

Apr 25, 2024 · Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. INTERSPEECH 2022: 3343-3347; 2021.

isca.png. Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language ... Using Deep Language Models and Transfer ...

Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language · Conference Paper · Full-text available. September ...

Apr 25, 2024 · Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. INTERSPEECH 2022: 3343-3347; 2021.

Apr 7, 2024 · In this paper, we analyze the application of test-time training (TTT) to improve robustness of models trained for depression detection.