Key result
Voice-based systems accurately estimate depressive states using three to four input utterances containing positive statements.
Why the study?
Mood changes affect voices, and short input voice is ideal to enable wide application of voice-based depression estimation methods.
Does a voice-based depression assessment system accurately estimate depressive states based on the number and type of input utterances?
Does a voice-based depression assessment system accurately estimate depressive states based on the number and type of input utterances?
A voice-based depression assessment system can accurately estimate depressive states using just three to four utterances if positive utterances are included.
Supports efficient voice-based depression estimation; leaves open validation before cardiovascular or clinical adoption.
It is empirically known that mood changes affect facial expressions and voices. In this study, the authors have focused on the voice to develop a method for estimating depression in individuals from their voices. A short input voice is ideal for applying the proposed method to a wide range of applications. Therefore, we evaluated this method using multiple input utterances while assuming a unit utterance input. The experimental results revealed that depressive states could be estimated with sufficient accuracy using the smallest number of utterances when positive utterances were included in three to four input utterances.
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Higuchi et al. (2021) studied Depression. Voice-based depression assessment system was evaluated on Estimation of depressive states. A voice-based depression assessment system estimated depressive states with sufficient accuracy when positive utterances were included in three to four input utterances.
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