MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox
Author:
Affiliation:
1. University of Augsburg, Augsburg, Germany
2. Nanyang Technological University, Singapore, Singapore
3. Imperial College London, London, United Kingdom
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3475957.3484451
Reference56 articles.
1. Mia Atcheson Vidhyasaharan Sethu and Julien Epps. 2018. Demonstrating and Modelling Systematic Time-varying Annotator Disagreement in Continuous Emotion Annotation. In Interspeech. 3668--3672. Mia Atcheson Vidhyasaharan Sethu and Julien Epps. 2018. Demonstrating and Modelling Systematic Time-varying Annotator Disagreement in Continuous Emotion Annotation. In Interspeech. 3668--3672.
2. FCM: The fuzzy c-means clustering algorithm
3. A Novel Method for Human Bias Correction of Continuous- Time Annotations
4. Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)
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