2015 International Conference on Affective Computing and Intelligent Interaction (ACII)最新文献_第10页

Gestural and Postural Reactions to Stressful Event: Design of a Haptic Stressful Stimulus 应激事件的手势和姿势反应:触觉应激刺激的设计

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344696

Yoren Gaffary, David Antonio Gómez Jáuregui, Jean-Claude Martin, M. Ammi

引用次数: 3

Adapting sentiment analysis to face-to-face human-agent interactions: From the detection to the evaluation issues 将情感分析应用于面对面的人机交互:从检测到评估问题

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344545

Caroline Langlet, C. Clavel

引用次数: 9

Cross-corpus analysis for acoustic recognition of negative interactions 负交互声识别的跨语料库分析

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344562

I. Lefter, H. Nefs, C. Jonker, L. Rothkrantz

{"title":"Cross-corpus analysis for acoustic recognition of negative interactions","authors":"I. Lefter, H. Nefs, C. Jonker, L. Rothkrantz","doi":"10.1109/ACII.2015.7344562","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344562","url":null,"abstract":"Recent years have witnessed a growing interest in recognizing emotions and events based on speech. One of the applications of such systems is automatically detecting when a situations gets out of hand and human intervention is needed. Most studies have focused on increasing recognition accuracies using parts of the same dataset for training and testing. However, this says little about how such a trained system is expected to perform `in the wild'. In this paper we present a cross-corpus study using the audio part of three multimodal datasets containing negative human-human interactions. We present intra- and cross-corpus accuracies whilst manipulating the acoustic features, normalization schemes, and oversampling of the least represented class to alleviate the negative effects of data unbalance. We observe a decrease in performance when disjunct corpora are used for training and testing. Merging two datasets for training results in a slightly lower performance than the best one obtained by using only one corpus for training. A hand crafted low dimensional feature set shows competitive behavior when compared to a brute force high dimensional features vector. Corpus normalization and artificially creating samples of the sparsest class have a positive effect.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"48 1","pages":"132-138"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78730588","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: 15

From simulated speech to natural speech, what are the robust features for emotion recognition? 从模拟语音到自然语音，情感识别的鲁棒性特征是什么?

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344597

Ya Li, Linlin Chao, Yazhu Liu, Wei Bao, J. Tao

{"title":"From simulated speech to natural speech, what are the robust features for emotion recognition?","authors":"Ya Li, Linlin Chao, Yazhu Liu, Wei Bao, J. Tao","doi":"10.1109/ACII.2015.7344597","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344597","url":null,"abstract":"The earliest research on emotion recognition starts with simulated/acted stereotypical emotional corpus, and then extends to elicited corpus. Recently, the demanding for real application forces the research shift to natural and spontaneous corpus. Previous research shows that accuracies of emotion recognition are gradual decline from simulated speech, to elicited and totally natural speech. This paper aims to investigate the effects of the common utilized spectral, prosody and voice quality features in emotion recognition with the three types of corpus, and finds out the robust feature for emotion recognition with natural speech. Emotion recognition by several common machine learning methods are carried out and thoroughly compared. Three feature selection methods are performed to find the robust features. The results on six common used corpora confirm that recognition accuracies decrease when the corpus changing from simulated to natural corpus. In addition, prosody and voice quality features are robust for emotion recognition on simulated corpus, while spectral feature is robust in elicited and natural corpus.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"64 1","pages":"368-373"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79580455","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: 19

Cognitive state measurement from eye gaze analysis in an intelligent virtual reality driving system for autism intervention 自闭症干预智能虚拟现实驾驶系统中眼注视分析的认知状态测量

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344621

Lian Zhang, Joshua W. Wade, A. Swanson, A. Weitlauf, Z. Warren, N. Sarkar

{"title":"Cognitive state measurement from eye gaze analysis in an intelligent virtual reality driving system for autism intervention","authors":"Lian Zhang, Joshua W. Wade, A. Swanson, A. Weitlauf, Z. Warren, N. Sarkar","doi":"10.1109/ACII.2015.7344621","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344621","url":null,"abstract":"Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disabilities with a high prevalence rate. While much research has focused on improving social communication deficits in ASD populations, less emphasis has been devoted to improving skills relevant for adult independent living, such as driving. In this paper, a novel virtual reality (VR)-based driving system with different difficulty levels of tasks is presented to train and improve driving skills of teenagers with ASD. The goal of this paper is to measure the cognitive load experienced by an individual with ASD while he is driving in the VR-based driving system. Several eye gaze features are identified that varied with cognitive load in an experiment participated by 12 teenagers with ASD. Several machine learning methods were compared and the ability of these methods to accurately measure cognitive load was validated with respect to the subjective rating of a therapist. Results will be used to build models in an intelligent VR-based driving system that can sense a participant's real-time cognitive load and offer driving tasks at an appropriate difficulty level in order to maximize the participant's long-term performance.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"51 1","pages":"532-538"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79395135","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: 12

Framework for combination aware AU intensity recognition 组合感知AU强度识别框架

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344631

Isabel Gonzalez, W. Verhelst, Meshia Cédric Oveneke, H. Sahli, D. Jiang

引用次数: 3

A warm touch of affect? 一种温暖的爱抚?

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344656

Christian J. A. M. Willemse

引用次数: 5

A linear regression model to detect user emotion for touch input interactive systems 基于线性回归模型的触摸输入交互系统用户情感检测

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344693

S. Bhattacharya

引用次数: 7

Building autonomous sensitive artificial listeners (Extended abstract) 构建自主敏感的人工听者(扩展摘要)

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344610

M. Schröder, Elisabetta Bevacqua, R. Cowie, F. Eyben, H. Gunes, D. Heylen, M. Maat, G. McKeown, Sathish Pammi, M. Pantic, C. Pelachaud, Björn Schuller, E. D. Sevin, M. Valstar, M. Wöllmer

{"title":"Building autonomous sensitive artificial listeners (Extended abstract)","authors":"M. Schröder, Elisabetta Bevacqua, R. Cowie, F. Eyben, H. Gunes, D. Heylen, M. Maat, G. McKeown, Sathish Pammi, M. Pantic, C. Pelachaud, Björn Schuller, E. D. Sevin, M. Valstar, M. Wöllmer","doi":"10.1109/ACII.2015.7344610","DOIUrl":"https://doi.org/10.1109/ACII.2015.7344610","url":null,"abstract":"This paper describes a substantial effort to build a real-time interactive multimodal dialogue system with a focus on emotional and non-verbal interaction capabilities. The work is motivated by the aim to provide technology with competences in perceiving and producing the emotional and non-verbal behaviours required to sustain a conversational dialogue. We present the Sensitive Artificial Listener (SAL) scenario as a setting which seems particularly suited for the study of emotional and non-verbal behaviour, since it requires only very limited verbal understanding on the part of the machine. This scenario allows us to concentrate on non-verbal capabilities without having to address at the same time the challenges of spoken language understanding, task modeling etc. We first summarise three prototype versions of the SAL scenario, in which the behaviour of the Sensitive Artificial Listener characters was determined by a human operator. These prototypes served the purpose of verifying the effectiveness of the SAL scenario and allowed us to collect data required for building system components for analysing and synthesising the respective behaviours. We then describe the fully autonomous integrated real-time system we created, which combines incremental analysis of user behaviour, dialogue management, and synthesis of speaker and listener behaviour of a SAL character displayed as a virtual agent. We discuss principles that should underlie the evaluation of SAL-type systems. Since the system is designed for modularity and reuse, and since it is publicly available, the SAL system has potential as a joint research tool in the affective computing research community.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"282 1","pages":"456-462"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88057551","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: 2

Multi-pose facial expression recognition based on SURF boosting 基于SURF增强的多姿态面部表情识别

2015 International Conference on Affective Computing and Intelligent Interaction (ACII) Pub Date : 2015-09-21 DOI: 10.1109/ACII.2015.7344635

Qiyu Rao, Xingtai Qu, Qi-rong Mao, Yongzhao Zhan

引用次数: 49