English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study explores a system that estimates the degree of decline for elderly persons using nonverbal information from daily conversations. Factors useful in estimating the degree of decline and methods of estimation need to be determined. First, we confirmed whether we can estimate the speaker’s age and “elderly likeness” from the conversation data. We made several processed conversation sounds: (“only included Fillers,” “only included Laughter utterances,” and “only included Intonation information”) from the original conversation database. By listening to these sounds, we confirmed that it is possible to estimate whether the speaker is young or elderly. Next, we analyzed the nonverbal features of conversation sounds of young and elderly individuals. In this paper, we selected the F0 and power value of “laughter utterance” and “speech utterance,” and compared the difference between young and elderly individuals. By comparing the results, we discussed the possibility of estimating a degree of decline.

Comparison of Non-verbal Feature of Free-conversation Speech between Elderly and Young Individuals