Speech Emotion Recognition in People at High Risk of Dementia.
Dement Neurocogn Disord
; 23(3): 146-160, 2024 Jul.
Article
en En
| MEDLINE
| ID: mdl-39113753
ABSTRACT
Background and Purpose:
The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia.Methods:
Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition.Results:
Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%.Conclusions:
The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Dement Neurocogn Disord
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Corea del Sur