{"title":"Training a Chatbot with Microsoft LUIS: Effect of Intent Imbalance on Prediction Accuracy","authors":"Elayne Ruane, Robert Young, Anthony Ventresque","doi":"10.1145/3379336.3381494","DOIUrl":"https://doi.org/10.1145/3379336.3381494","url":null,"abstract":"Microsoft LUIS is a natural language understanding service used to train Chatbots. Imbalance in the utterance training set may cause the LUIS model to predict the wrong intent for a user's query. We discuss this problem and the training recommendations from Microsoft to improve prediction accuracy with LUIS. We perform batch testing on three training sets created from two existing datasets to explore the effectiveness of these recommendations.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124826843","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}
Alison Smith-Renner, S. Kleanthous, Brian Y. Lim, T. Kuflik, S. Stumpf, Jahna Otterbacher, Advait Sarkar, Casey Dugan, Avital Shulner Tal
{"title":"ExSS-ATEC: Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies 2020","authors":"Alison Smith-Renner, S. Kleanthous, Brian Y. Lim, T. Kuflik, S. Stumpf, Jahna Otterbacher, Advait Sarkar, Casey Dugan, Avital Shulner Tal","doi":"10.1145/3379336.3379361","DOIUrl":"https://doi.org/10.1145/3379336.3379361","url":null,"abstract":"Smart systems that apply complex reasoning to make decisions and plan behavior, such as decision support systems and personalized recommendations, are difficult for users to understand. Algorithms allow the exploitation of rich and varied data sources, in order to support human decision-making and/or taking direct actions; however, there are increasing concerns surrounding their transparency and accountability, as these processes are typically opaque to the user. Transparency and accountability have attracted increasing interest to provide more effective system training, better reliability and improved usability. This workshop will provide a venue for exploring issues that arise in designing, developing and evaluating intelligent user interfaces that provide system transparency or explanations of their behavior. In addition, our goal is to focus on approaches to mitigate algorithmic biases that can be applied by researchers, even without access to a given system's inter-workings, such as awareness, data provenance, and validation.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114398102","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}
{"title":"User Experience Evaluation through Automatic A/B Testing","authors":"Juan Cruz Gardey, A. Garrido","doi":"10.1145/3379336.3381514","DOIUrl":"https://doi.org/10.1145/3379336.3381514","url":null,"abstract":"The goal of this research is to develop an A/B testing method to automatically compare the user experience (UX) of alternative designs for a web application in a real context with a large number of users. The challenge that it poses is to find mechanisms to predict the UX with machine learning techniques. This submission outlines the motivation, research goal, current status and remaining work.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134572471","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}
Cosmin Munteanu, L. Clark, Benjamin Cowan, Stephan Schlögl, M. I. Torres, Justin Edwards, Christine Murad, M. Aylett, Martin Porcheron, Heloisa Candello, Philip R. Doyle, Jaisie Sin
{"title":"CUI","authors":"Cosmin Munteanu, L. Clark, Benjamin Cowan, Stephan Schlögl, M. I. Torres, Justin Edwards, Christine Murad, M. Aylett, Martin Porcheron, Heloisa Candello, Philip R. Doyle, Jaisie Sin","doi":"10.1145/3379336.3379358","DOIUrl":"https://doi.org/10.1145/3379336.3379358","url":null,"abstract":"The use of speech as an interaction modality has grown considerably through the integration of Intelligent Personal Assistants (IPAs- e.g. Siri, Google Assistant) into smartphones and voice based devices (e.g. Amazon Echo). Such engineering advances in speech processing present a unique opportunity for enabling users to interact with interface in a truly conversational way. However, we have yet to see current voice-enable interface fully becoming Conversational User Interfaces (CUIs) as afforded by the underlying speech and natural language capabilities. For example, from a conversational / dialogue perspective, there remain significant gaps in using theoretical frameworks to understand user behaviours and choices and how they may applied to specific speech interface interactions. On a design and Human-Computer Interaction level, we don't yet have the proper tools such as validated design guidelines to help us improve the usability of such interfaces. On the speech processing side, variability in speech, language, and conversation still pose problem, and error-recovery strategies often lead to degraded user experience. From a critical perspective, issues of ethics and privacy remain yet to be addressed.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126078179","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}
{"title":"FRISP","authors":"Junghyun Byun, Hyocheol Ro, T. Han","doi":"10.1145/3379336.3381458","DOIUrl":"https://doi.org/10.1145/3379336.3381458","url":null,"abstract":"Projection-based augmented reality (AR) is a promising medium for realizing pervasive computing environment, and yet the problem of determining projection-suitable regions and where to project remains. To tackle this problem, we introduce FRISP, a projection-based augmented reality (AR) Framework designed for Registering Interactive Spatial Projection. The FRISP framework utilizes a pantilt projection-camera (pro-cam) system for capturing geometry and projection mapping. The framework scans and analyzes the geometric properties of a room, in order to determine projection-suitable regions and generate multi-window layouts. Once the multi-windows are registered to the real world, they can be interacted with by the users. The users can assign various widgets or applications to the multi-windows, which are then finally augmented onto the real world and can serve as a base units for realizing the pervasive AR environment.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130980268","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}
{"title":"Am I Asking It Properly?: Designing and Evaluating Interview Chatbots to Improve Elicitation in an Ethical Way","authors":"Xu Han","doi":"10.1145/3379336.3381509","DOIUrl":"https://doi.org/10.1145/3379336.3381509","url":null,"abstract":"The increasingly prevalent use of chatbots provides an innovative way to conduct conversation interviews. However, the lack of comprehensive design guidance and robust evaluation methodologies challenge designers in developing interview chatbots with good elicitation and ethics. This proposal presents our progress on investigating interview chatbots' performances in eliciting high-quality response without breaking any ethical rules, based on which an automatic evaluation framework will be developed. We also present our plan to propose design implications and prototypes for more robust interview chatbot development cycle.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"108 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123229018","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}
Dakuo Wang, P. Ram, D. Weidele, Sijia Liu, Michael J. Muller, Justin D. Weisz, Abel N. Valente, Arunima Chaudhary, Dustin Torres, H. Samulowitz, Lisa Amini
{"title":"AutoAI","authors":"Dakuo Wang, P. Ram, D. Weidele, Sijia Liu, Michael J. Muller, Justin D. Weisz, Abel N. Valente, Arunima Chaudhary, Dustin Torres, H. Samulowitz, Lisa Amini","doi":"10.1145/3379336.3381474","DOIUrl":"https://doi.org/10.1145/3379336.3381474","url":null,"abstract":"Automated Artificial Intelligence and Machine Learning (AutoAI / AutoML) can now automate every step of the end-to-end AI Lifecycle, from data cleaning, to algorithm selection, and to model deployment and monitoring in the machine learning workflow. AutoAI technologies, initially aimed to save data scientists from the low level coding tasks, also has great potential to serve non-technical users such as domain experts and business users to build and deploy machine learning models. Researchers coined it as \"democratizing AI\", where non-technical users are empowered by AutoAI technologies to create and adopt AI models. To realize such promise, AutoAI needs to translate and incorporate the real-world business logic and requirements into the automation. In this Demo, we present a first of its kinds experimental system, IBM AutoAI Playground, that enables non-technical users to define and customize their business goals (e.g., Prediction Time) as constraints. AutoAI then builds models to satisfy those constraints while optimizing for the model performance (e.g., ROC AUC score). This Demo also showcases AutoAIViz, a Conditional Parallel Coordinates visualization feature, and a TrustedAI feature from two accepted IUI'20 papers.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126946853","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}
{"title":"Bayesian Methods in Interaction Design (Tutorial)","authors":"John Williamson, Antti Oulasvirta, P. Kristensson","doi":"10.1145/3379336.3379354","DOIUrl":"https://doi.org/10.1145/3379336.3379354","url":null,"abstract":"This tutorial introduces Bayesian computational approaches to interaction and design. Bayesian methods offer a powerful approach for interactive settings with uncertainty and noise. This course introduces the theory and practice of computational Bayesian interaction, covering inference of user data and design/adaptation of interface features based around probabilistic inference. The tutorial is built around hands-on Python programming with modern computational tools, interleaved with theory and practical examples grounded in problems of wide interest in human-computer interaction.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127171021","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}
Mathias Wilhelm, Jan-Peter Lechler, Daniel G. Krakowczyk, S. Albayrak
{"title":"Demonstration of Finger Tracking Using Capacitive Sensing with a Ring","authors":"Mathias Wilhelm, Jan-Peter Lechler, Daniel G. Krakowczyk, S. Albayrak","doi":"10.1145/3379336.3381475","DOIUrl":"https://doi.org/10.1145/3379336.3381475","url":null,"abstract":"In this demo paper, we present a demonstrator for a ring-based finger tracking approach. The demonstrator consists of a ring-shaped interaction device, called PeriSense, utilizing capacitive sensing in order to enable finger tracking. The motion of the finger wearing the ring and the adjacent fingers is sensed by measuring the capacitive proximity between the electrodes and the human skin. To map the capacitive measurements to the finger angles, we apply a regression model based on long short-term memory (LSTM). A virtual 3D hand model renders simultaneous the predicted finger angles.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133872279","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}
Yuya Komabashiri, T. Mashita, P. Ratsamee, Yuuki Uranishi, M. Koike, Kiyoyasu Maruyama
{"title":"Optimal Arrangement of Surveillance Cameras Using Space Division and a Genetic Algorithm","authors":"Yuya Komabashiri, T. Mashita, P. Ratsamee, Yuuki Uranishi, M. Koike, Kiyoyasu Maruyama","doi":"10.1145/3379336.3381488","DOIUrl":"https://doi.org/10.1145/3379336.3381488","url":null,"abstract":"This paper presents an optimal camera arrangement method for surveillance camera systems that evaluates the arrangement of cameras in 3D space. It makes use of multiple factors and optimizes this arrangement using a genetic algorithm (GA). We implemented a prototype in Unity that demonstrates our proposed method, and experiments show the performance of our method when used for placement in a virtual environment.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126966271","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}