Adaptive Data Boosting Technique for Robust Personalized Speech Emotion in Emotionally-Imbalanced Small-Sample Environments

Adaptive Data Boosting Technique for Robust Personalized Speech Emotion in Emotionally-Imbalanced Small-Sample Environments

Personalized emotion recognition provides an individual training model for each target user in order to mitigate the accuracy problem when using general training models collected from multiple users. Existing personalized speech emotion recognition research has a cold-start problem that requires a l...

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Bibliographic Details
Main Authors: Jaehun Bang, Taeho Hur, Dohyeong Kim, Thien Huynh-The, Jongwon Lee, Yongkoo Han, Oresti Banos, Jee-In Kim, Sungyoung Lee
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Sensors
Subjects:
speech emotion recognition
personalization
machine learning
data selection
data augmentation
Online Access:https://www.mdpi.com/1424-8220/18/11/3744

Internet

https://www.mdpi.com/1424-8220/18/11/3744

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