Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop最新文献

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3286909

F. Ringeval

引用次数: 0

Bipolar Disorder Recognition via Multi-scale Discriminative Audio Temporal Representation 基于多尺度判别音频时间表征的双相情感障碍识别

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3266302.3268997

Zhengyin Du, Weixin Li, Di Huang, Yunhong Wang

引用次数: 26

Session details: Bipolar Disorder Sub-challenge 会议细节:双相情感障碍子挑战

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3286911

F. Ringeval

引用次数: 0

Session details: Gold-standard Emotion Sub-challenge 会话细节:黄金标准的情感子挑战

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3286913

F. Ringeval

引用次数: 0

Session details: Cross-cultural Emotion Sub-challenge 会议细节:跨文化情感子挑战

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3286912

C. Lee

引用次数: 0

Fusing Annotations with Majority Vote Triplet Embeddings 用多数票三联体嵌入融合注释

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3266302.3266312

Brandon M. Booth, Karel Mundnich, Shrikanth S. Narayanan

{"title":"Fusing Annotations with Majority Vote Triplet Embeddings","authors":"Brandon M. Booth, Karel Mundnich, Shrikanth S. Narayanan","doi":"10.1145/3266302.3266312","DOIUrl":"https://doi.org/10.1145/3266302.3266312","url":null,"abstract":"Human annotations of behavioral constructs are of great importance to the machine learning community because of the difficulty in quantifying states that cannot be directly observed, such as dimensional emotion. Disagreements between annotators and other personal biases complicate the goal of obtaining an accurate approximation of the true behavioral construct values for use as ground truth. We present a novel majority vote triplet embedding scheme for fusing real-time and continuous annotations of a stimulus to produce a gold-standard time series. We illustrate the validity of our approach by showing that the method produces reasonable gold-standards for two separate annotation tasks from a human annotation data set where the true construct labels are known a priori. We also apply our method to the RECOLA dimensional emotion data set in conjunction with state-of-the-art time warping methods to produce gold-standard labels that are sufficiently representative of the annotations and also that are more easily learned from features when evaluated using a battery of linear predictors as prescribed in the 2018 AVEC gold-standard emotion sub-challenge. In particular, we find that the proposed method leads to gold-standard labels that aid in valence prediction.","PeriodicalId":123523,"journal":{"name":"Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121495533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Automated Screening for Bipolar Disorder from Audio/Visual Modalities 双相情感障碍音频/视觉模式的自动筛查

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3266302.3266315

Zafi Sherhan Syed, K. Sidorov, David Marshall

引用次数: 29

Session details: Introduction 会议详情:

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3286910

C. Lee

引用次数: 0

Multi-modal Multi-cultural Dimensional Continues Emotion Recognition in Dyadic Interactions 多模态多文化维度继续着二元互动中的情感识别

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3266302.3266313

Jinming Zhao, Ruichen Li, Shizhe Chen, Qin Jin

{"title":"Multi-modal Multi-cultural Dimensional Continues Emotion Recognition in Dyadic Interactions","authors":"Jinming Zhao, Ruichen Li, Shizhe Chen, Qin Jin","doi":"10.1145/3266302.3266313","DOIUrl":"https://doi.org/10.1145/3266302.3266313","url":null,"abstract":"Automatic emotion recognition is a challenging task which can make great impact on improving natural human computer interactions. In this paper, we present our solutions for the Cross-cultural Emotion Sub-challenge (CES) of Audio/Visual Emotion Challenge (AVEC) 2018. The videos were recorded in dyadic human-human interaction scenarios. In these complicated scenarios, a person's emotion state will be influenced by the interlocutor's behaviors, such as talking style/prosody, speech content, facial expression and body language. In this paper, we highlight two aspects of our solutions: 1) we explore multiple modalities's efficient deep learning features and use the LSTM network to capture the long-term temporal information. 2) we propose several multimodal interaction strategies to imitate the real interaction patterns for exploring which modality information of the interlocutor is effective, and we find the best interaction strategy which can make full use of the interlocutor's information. Our solutions achieve the best CCC performance of 0.704 and 0.783 on arousal and valence respectively on the challenge testing set of German, which significantly outperform the baseline system with corresponding CCC of 0.524 and 0.577 on arousal and valence, and which outperform the winner of the AVEC2017 with corresponding CCC of 0.675 and 0.756 on arousal and valence. The experimental results show that our proposed interaction strategies have strong generalization ability and can bring more robust performance.","PeriodicalId":123523,"journal":{"name":"Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126339639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 35

Multi-modality Hierarchical Recall based on GBDTs for Bipolar Disorder Classification 基于GBDTs的双相情感障碍分类多模态层次查全

Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop Pub Date : 2018-10-15 DOI: 10.1145/3266302.3266311

Xiaofen Xing, Bolun Cai, Yinhu Zhao, Shuzhen Li, Zhiwei He, Weiquan Fan

引用次数: 20