2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)最新文献_第3页

Emotional Paraphrasing Using Pre-trained Language Models 使用预先训练的语言模型进行情感解释

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666309

Jacky Casas, Samuel Torche, Karl Daher, E. Mugellini, Omar Abou Khaled

{"title":"Emotional Paraphrasing Using Pre-trained Language Models","authors":"Jacky Casas, Samuel Torche, Karl Daher, E. Mugellini, Omar Abou Khaled","doi":"10.1109/aciiw52867.2021.9666309","DOIUrl":"https://doi.org/10.1109/aciiw52867.2021.9666309","url":null,"abstract":"Emotion style transfer is a recent and challenging problem in Natural Language Processing (NLP). Transformer-based language models are becoming extremely powerful, so one wonders if it would be possible to leverage them to perform emotion style transfer. So far, previous work has not used transformer-based models for this task. To address this task, we fine-tune a GPT-2 model with corrupted emotional data. This will train the model to increase the emotional intensity of the input sentence. Coupled with a paraphrasing model, we develop a system capable of transferring an emotion into a paraphrase. We conducted a qualitative study with human judges, as well as a quantitative evaluation. Although the paraphrase metrics show poor performance compared to the state of the art, the transfer of emotion proved to be effective, especially for the emotions fear, sadness, and disgust. The perception of these emotions were improved both in the automatic and human evaluations. Such technology can significantly facilitate the automatic creation of training sentences for natural language understanding (NLU) systems, but it can also be integrated into an emotional or empathic dialogue architecture.","PeriodicalId":105376,"journal":{"name":"2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133979716","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: 3

Real-time Ubiquitous Pain Recognition 实时无处不在的疼痛识别

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666289

Iyonna Tynes, Shaun J. Canavan

引用次数: 0

Detection of Nudges and Measuring of Alignment in Spoken Interactions 在口语互动中检测暗示和测量对齐度

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666344

N. Kalashnikova

引用次数: 1

A system for collecting emotionally annotated physiological signals in daily life using wearables 一种利用可穿戴设备收集日常生活中带有情感注释的生理信号的系统

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666272

Stanisław Saganowski, Maciej Behnke, Joanna Komoszyńska, Dominika Kunc, Bartosz Perz, Przemyslaw Kazienko

引用次数: 8

A simple baseline for evaluating Expression Transfer and Anonymisation in Video Transfer 评价视频传输中表达转移和匿名化的简单基线

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666292

Gabriel Haddon-Hill, Keerthy Kusumam, M. Valstar

{"title":"A simple baseline for evaluating Expression Transfer and Anonymisation in Video Transfer","authors":"Gabriel Haddon-Hill, Keerthy Kusumam, M. Valstar","doi":"10.1109/aciiw52867.2021.9666292","DOIUrl":"https://doi.org/10.1109/aciiw52867.2021.9666292","url":null,"abstract":"Video-to-video synthesis methods provide increasingly accessible solutions for training models on privacy-sensitive and limited-size datasets frequently encountered in domains such as affect analysis. However, there are no existing baselines that explicitly measure the extent of reliable expression transfer or privacy preservation in the generated data. In this paper, we evaluate a general-purpose video transfer method, vid2vid, on these two key tasks: expression transfer and anonymisation of identities, as well as its suitability for training affect prediction models. We provide results that form a strong baseline for future comparisons, and further motivate the need for purpose-built methods for conducting expression-preserving video transfer. Our results indicate that a significant limitation of vid2vid's expression transfer arises from conditioning on facial landmarks and optical flow, which do not carry sufficient information to preserve facial expressions. Finally, we demonstrate that vid2vid can adequately anonymise videos in some cases, though not consistently, and that the anonymisation can be improved by applying random perturbations to input landmarks, at the cost of reduced expression transfer.","PeriodicalId":105376,"journal":{"name":"2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115489477","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: 0

SUGO-MIMI: A Waggle Ear-Type Device Linked to Eyebrows SUGO-MIMI:与眉毛相连的摆动耳朵式装置

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666368

Shoko Kimura, Ayaka Fujii, Seiichi Harata, Takuto Sakuma, Shohei Kato

引用次数: 0

Relationship between Mood Improvement and Questioning to Evaluate Automatic Thoughts in Cognitive Restructuring with a Virtual Agent 基于虚拟Agent的认知重构中自动思维的情绪改善与质疑的关系

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666312

Kazuhiro Shidara, Hiroki Tanaka, Hiroyoshi Adachi, D. Kanayama, Yukako Sakagami, Takashi Kudo, Satoshi Nakamura

{"title":"Relationship between Mood Improvement and Questioning to Evaluate Automatic Thoughts in Cognitive Restructuring with a Virtual Agent","authors":"Kazuhiro Shidara, Hiroki Tanaka, Hiroyoshi Adachi, D. Kanayama, Yukako Sakagami, Takashi Kudo, Satoshi Nakamura","doi":"10.1109/aciiw52867.2021.9666312","DOIUrl":"https://doi.org/10.1109/aciiw52867.2021.9666312","url":null,"abstract":"Cognitive restructuring is a therapeutic technique of cognitive behavior therapy that helps convert negative automatic thoughts to balanced thoughts. Automatic thoughts can be converted by the patient/participant's own objective evaluation from a different perspective. Human therapists ask questions intending to guide the evaluation of automatic thoughts more effectively. Virtual agents, as therapists, have a great potential to support cognitive restructuring. We investigated how a virtual agent could affect the participant's mood when asked questions to evaluate automatic thoughts in cognitive restructuring. We implemented a virtual agent that performs scenario-based dialogue with two types of dialogue scenarios: with and without questions to evaluate automatic thoughts. We conducted a dialogue experiment with 20 healthy graduate students and divided them into two groups of ten, finding that the participant's negative mood significantly improved when the virtual agent asked questions to evaluate the automatic thoughts. Furthermore, the number of helpful questions was significantly correlated with the degree of mood change (ρ=0.81). The results suggest that it is important to provide appropriate questions for cognitive restructuring and that the number of helpful questions reflects the dialogue's effectiveness.","PeriodicalId":105376,"journal":{"name":"2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128962814","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: 3

A Multimodal Engagement-Aware Recommender System for People with Dementia 痴呆患者多模式参与感知推荐系统

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666306

Lars Steinert

引用次数: 1

Quantifying the Intensity of Toxicity for Discussions and Speakers 量化讨论和演讲者的毒性强度

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666258

Samiha Samrose, E. Hoque

{"title":"Quantifying the Intensity of Toxicity for Discussions and Speakers","authors":"Samiha Samrose, E. Hoque","doi":"10.1109/aciiw52867.2021.9666258","DOIUrl":"https://doi.org/10.1109/aciiw52867.2021.9666258","url":null,"abstract":"In this work, from YouTube News-show multimodal dataset with dyadic speakers having heated discussions, we analyze the toxicity through audio-visual signals. Firstly, as different speakers may contribute differently towards the toxicity, we propose a speaker-wise toxicity score revealing individual proportionate contribution. As discussions with disagreements may reflect some signals of toxicity, in order to identify discussions needing more attention we categorize discussions into binary high-low toxicity levels. By analyzing visual features, we show that the levels correlate with facial expressions as Upper Lid Raiser (associated with ‘surprise’), Dimpler (associated with ‘contempť), and Lip Corner Depressor (associated with ‘disgust’) remain statistically significant in separating high-low intensities of disrespect. Secondly, we investigate the impact of audio-based features such as pitch and intensity that can significantly elicit disrespect, and utilize the signals in classifying disrespect and non-disrespect samples by applying logistic regression model achieving 79.86% accuracy. Our findings shed light on the potential of utilizing audio-visual signals in adding important context towards understanding toxic discussions.","PeriodicalId":105376,"journal":{"name":"2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123559581","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: 1

Embracing and Exploiting Annotator Emotional Subjectivity: An Affective Rater Ensemble Model 拥抱和开发注释者情感主体性:一个情感评注者的整体模型

2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) Pub Date : 2021-09-28 DOI: 10.1109/aciiw52867.2021.9666407

Lukas Stappen, Lea Schumann, A. Batliner, Björn Schuller

{"title":"Embracing and Exploiting Annotator Emotional Subjectivity: An Affective Rater Ensemble Model","authors":"Lukas Stappen, Lea Schumann, A. Batliner, Björn Schuller","doi":"10.1109/aciiw52867.2021.9666407","DOIUrl":"https://doi.org/10.1109/aciiw52867.2021.9666407","url":null,"abstract":"Automated recognition of continuous emotions in audio-visual data is a growing area of study that aids in understanding human-machine interaction. Training such systems presupposes human annotation of the data. The annotation process, however, is laborious and expensive given that several human ratings are required for every data sample to compensate for the subjectivity of emotion perception. As a consequence, labelled data for emotion recognition are rare and the existing corpora are limited when compared to other state-of-the-art deep learning datasets. In this study, we explore different ways in which existing emotion annotations can be utilised more effectively to exploit available labelled information to the fullest. To reach this objective, we exploit individual raters’ opinions by employing an ensemble of rater-specific models, one for each annotator, by that reducing the loss of information which is a byproduct of annotation aggregation; we find that individual models can indeed infer subjective opinions. Furthermore, we explore the fusion of such ensemble predictions using different fusion techniques. Our ensemble model with only two annotators outperforms the regular Arousal baseline on the test set of the MuSe-CaR corpus. While no considerable improvements on valence could be obtained, using all annotators increases the prediction performance of arousal by up to. 07 Concordance Correlation Coefficient absolute improvement on test - solely trained on rate-specific models and fused by an attention-enhanced Long-short Term Memory-Recurrent Neural Network.","PeriodicalId":105376,"journal":{"name":"2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123786951","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: 0