Výsledky vyhledávání - "CANDY OLIVIA, MAWALIM"

Akademický článek

MAG-BERT-ARL for Fair Automated Video Interview Assessment

Autor: Bimasena Putra, Kurniawati Azizah, Candy Olivia Mawalim, Ikhlasul Akmal Hanif, Sakriani Sakti, Chee Wee Leong, Shogo Okada

Publikováno v: IEEE Access, Vol 12, Pp 145188-145205 (2024)

Potential biases within automated video interview assessment algorithms may disadvantage specific demographics due to the collection of sensitive attributes, which are regulated by the General Data Protection Regulation (GDPR). To mitigate these fair

Externí odkaz: https://doaj.org/article/2dbb3cb8e5334eee89b76ac03645fecc

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Akademický článek

A Ranking Model for Evaluation of Conversation Partners Based on Rapport Levels

Autor: Takato Hayashi, Candy Olivia Mawalim, Ryo Ishii, Akira Morikawa, Atsushi Fukayama, Takao Nakamura, Shogo Okada

Publikováno v: IEEE Access, Vol 11, Pp 73024-73035 (2023)

Our proposed ranking model ranks conversation partners based on self-reported rapport levels for each participant. The model is important for tasks that recommend interaction partners based on user rapport built in past interactions, such as matchmak

Externí odkaz: https://doaj.org/article/224909839d4545adb2444aebc6f3de2e

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Akademický článek

Speech Watermarking Method Using McAdams Coefficient Based on Random Forest Learning

Autor: Candy Olivia Mawalim, Masashi Unoki

Publikováno v: Entropy, Vol 23, Iss 10, p 1246 (2021)

Speech watermarking has become a promising solution for protecting the security of speech communication systems. We propose a speech watermarking method that uses the McAdams coefficient, which is commonly used for frequency harmonics adjustment. The

Externí odkaz: https://doaj.org/article/72107cc2380b439687b90a8645215a4d

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Personality trait estimation in group discussions using multimodal analysis and speaker embedding

Autor: Candy Olivia Mawalim, Shogo Okada, Yukiko I. Nakano, Masashi Unoki

Publikováno v: Journal on Multimodal User Interfaces.

The automatic estimation of personality traits is essential for many human–computer interface (HCI) applications. This paper focused on improving Big Five personality trait estimation in group discussions via multimodal analysis and transfer learni

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d22c4dcfee472024694e721bc6ab4e37
https://doi.org/10.1007/s12193-023-00401-0

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