ABSTRACT
Conversational Agents (CAs) employing voice as their main interaction mode produce natural language utterances with the aim of mimicking human conversations. To unveil hiccups in conversations with recommender systems, we observed users interacting with CAs. Our findings suggest that those occur as users struggle to start the session, as CAs do not appear exploratory, and as CAs remained silent after offering recommendation(s) or after reporting errors. Users enacted mental models derived from years of experience with Graphical User Interfaces, but also expected human-like characteristics such as explanations and proactivity. Anchoring on these, we designed a dialogue model for a multimodal Conversational Recommender System (CRS) mimicking humans and GUIs. We probed the state of hiccups further with a Wizard-of-Oz prototype implementing this dialogue model. Our findings suggest that participants rapidly adopted GUI mimicries, cooperated for error resolution, appreciated explainable recommendations, and provided insights to improve persisting hiccups in proactivity and navigation. Based on these, we provide implications for design to address hiccups in CRS.
Supplemental Material
- Leif Azzopardi, Mateusz Dubiel, Martin Halvey, and Jeffrey Dalton. Conceptualizing agent-human interactions during the conversational search process. In SIGIR 2nd International Workshop on Conversational Approaches to Information Retrieval (CAIR’18), 2018. 8 pages.Google Scholar
- Anton Batliner, Christian Hacker, and Elmar Nöth. 2008. To talk or not to talk with a computer: Taking into account the user's focus of attention. Journal on Multimodal User Interfaces 2, 3–4: 171–186. https://doi.org/10.1007/s12193-009-0016-6Google ScholarCross Ref
- Grace M. Begany, Ning Sa, and Xiaojun Yuan. 2015. Factors Affecting User Perception of a Spoken Language vs. Textual Search Interface: A Content Analysis. Interacting with Computers: iwv029. https://doi.org/10.1093/iwc/iwv029Google Scholar
- M. M. Bekker, F. L. Van Nes, and J. F. Juola. 1995. A comparison of mouse and speech input control of a text-annotation system. Behaviour & Information Technology 14, 1: 14–22. https://doi.org/10.1080/01449299508914621Google ScholarCross Ref
- Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health 11, 4 (2019), 589–597. http://dx.doi.org/10.1080/2159676X.2019.1628806Google ScholarCross Ref
- Marion Buchenau and Jane Fulton Suri. 2000. Experience prototyping. In Proceedings of the 3rd conference on Designing interactive systems: processes, practices, methods, and techniques (DIS ’00). Association for Computing Machinery, New York, NY, USA, 424–433. https://doi.org/10.1145/347642.347802Google ScholarDigital Library
- Julia Cambre, Alex C Williams, Afsaneh Razi, Ian Bicking, Abraham Wallin, Janice Tsai, Chinmay Kulkarni, and Jofish Kaye. 2021. Firefox Voice: An Open and Extensible Voice Assistant Built Upon the Web. In CHI Conference on Human Factors in Computing Systems (CHI '21), May 8–13, 2021, Yokohama, Japan. ACM, New York, NY, USA 18 Pages. https://doi.org/10.1145/3411764.3445409Google ScholarDigital Library
- Minsuk Chang, Anh Truong, Oliver Wang, Maneesh Agrawala, and Juho Kim. 2019. How to Design Voice Based Navigation for How-To Videos. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Paper 701, 1–11. https://doi.org/10.1145/3290605.3300931Google ScholarDigital Library
- Zhongxia Chen, Xiting Wang, Xing Xie, Mehul Parsana, Akshay Soni, Xiang Ao, Enhong Chen. 2020. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI’20). Main track. Pages 2994-3000. https://doi.org/10.24963/ijcai.2020/414.Google Scholar
- Eugene Cho. 2019. Hey Google, Can I Ask You Something in Private? In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19, 1–9. https://doi.org/10.1145/3290605.3300488Google ScholarDigital Library
- Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann. 2016. Towards Conversational Recommender Systems. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16). Association for Computing Machinery, New York, NY, USA, 815–824. https://doi.org/10.1145/2939672.2939746Google ScholarDigital Library
- Leigh Clark, Philip Doyle, Diego Garaialde, Emer Gilmartin, Stephan Schlögl, Jens Edlund, Matthew Aylett, João Cabral, Cosmin Munteanu, Justin Edwards, and Benjamin R Cowan. 2019. The State of Speech in HCI: Trends, Themes and Challenges. Interacting with Computers. https://doi.org/10.1093/iwc/iwz016Google Scholar
- Leigh Clark, Cosmin Munteanu, Vincent Wade, Benjamin R. Cowan, Nadia Pantidi, Orla Cooney, Philip Doyle, Diego Garaialde, Justin Edwards, Brendan Spillane, Emer Gilmartin, and Christine Murad. 2019. What Makes a Good Conversation?: Challenges in Designing Truly Conversational Agents. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19, 1–12. https://doi.org/10.1145/3290605.3300705Google ScholarDigital Library
- Computer terms, dictionary and glossary. Retrieved 24 February 2021 from https://www.computerhope.com/jargon.htmlGoogle Scholar
- Benjamin R. Cowan, Nadia Pantidi, David Coyle, Kellie Morrissey, Peter Clarke, Sara Al-Shehri, David Earley, and Natasha Bandeira. 2017. “What can i help you with?”: infrequent users’ experiences of intelligent personal assistants. In Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services - MobileHCI ’17, 1–12. https://doi.org/10.1145/3098279.3098539Google ScholarDigital Library
- Ireland D, Atay C, Liddle J, Bradford D, Lee H, Rushin O, Mullins T, Angus D, Wiles J, McBride S, Vogel A. Hello Harlie: Enabling Speech Monitoring Through Chat-Bot Conversations. Stud Health Technol Inform. 2016;227:55-60. PMID: 27440289.Google Scholar
- Zuohui Fu, Yikun Xian, Yongfeng Zhang, and Yi Zhang. 2020. Tutorial on Conversational Recommendation Systems. In Fourteenth ACM Conference on Recommender Systems (RecSys '20). Association for Computing Machinery, New York, NY, USA, 751–753. https://doi.org/10.1145/3383313.3411548Google ScholarDigital Library
- Souvick Ghosh. 2019. Investigating Result Presentation in Conversational IR. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval (CHIIR '19). Association for Computing Machinery, New York, NY, USA, 421–424. https://doi.org/10.1145/3295750.3298974Google ScholarDigital Library
- Mehmet Göker and Cynthia Thompson. 2000. The adaptive place advisor: A conversational recommendation system. In Proceedings of the 8th German Workshop on Case Based Reasoning. 187–198Google Scholar
- Dwayne D. Gremler. 2004. The Critical Incident Technique in Service Research. Journal of Service Research 7, 1: 65–89. https://doi.org/10.1177/1094670504266138Google ScholarCross Ref
- Ido Guy. The characteristics of voice search: Comparing spoken with typed-in mobile web search queries. ACM Transactions on Information Systems (TOIS), 36(3):30:1–30:28, 2018. https://doi.org/10.1145/3182163Google ScholarDigital Library
- Susumu Harada, Jacob O. Wobbrock, Jonathan Malkin, Jeff A. Bilmes, and James A. Landay. 2009. Longitudinal study of people learning to use continuous voice-based cursor control. In Proceedings of the 27th international conference on Human factors in computing systems - CHI 09, 347. https://doi.org/10.1145/1518701.1518757Google ScholarDigital Library
- Jiang Hu, Andi Winterboer, Clifford I. Nass, Johanna D. Moore, and Rebecca Illowsky. 2007. Context & usability testing: user-modeled information presentation in easy and difficult driving conditions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI ’07, 1343–1346. https://doi.org/10.1145/1240624.1240827Google ScholarDigital Library
- Razan Jaber and Donald McMillan. 2020. Conversational User Interfaces on Mobile Devices: Survey. In Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20). Association for Computing Machinery, New York, NY, USA, Article 10, 1–11. https://doi.org/10.1145/3405755.3406130Google ScholarDigital Library
- Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, and Li Chen. 2021. A Survey on Conversational Recommender Systems. ACM Comput. Surv. 54, 5, Article 105 (June 2021), 36 pages. https://doi.org/10.1145/3453154Google ScholarDigital Library
- Joseph “Jofish” Kaye, Joel Fischer, Jason Hong, Frank R. Bentley, Cosmin Munteanu, Alexis Hiniker, Janice Y. Tsai, and Tawfiq Ammari. 2018. Panel: Voice Assistants, UX Design and Research. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18, 1–5. https://doi.org/10.1145/3170427.3186323Google ScholarDigital Library
- Dan Jurafsky and James H. Martin, Speech and Language Processing (3rd ed. draft), Chapter 26 (Dialog Systems and Chatbots), 2019 (https://web.stanford.edu/∼jurafsky/slp3/26.pdf)Google Scholar
- Abhishek Kaushik and Gareth J. F. Jones. 2018. Exploring Current User Web Search Behaviours in Analysis Tasks to be Supported in Conversational Search. In Second International Workshop on Conversational Approaches to Information Retrieval (CAIR’18), July 12, 2018, Ann Arbor Michigan, USA. ACM, New York, NY, USA, Article 4, 8 pages. https://doi.org/10.48550/arXiv.2104.04501Google Scholar
- Philipp Kirschthaler, Martin Porcheron, and Joel E. Fischer. 2020. What Can I Say? Effects of Discoverability in VUIs on Task Performance and User Experience. In Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20). Association for Computing Machinery, New York, NY, USA, Article 9, 1–9. https://doi.org/10.1145/3405755.3406119Google ScholarDigital Library
- Raina Langevin, Ross Lordon, Thi Avrahami, Benjamin Cowan, Tad Hirsch, and Gary Hsieh. 2021. Heuristic Evaluation of Conversational Agents. In CHI ’21: ACM CHI Conference on Human Factors in Computing Systems, May 8–13, 2021, Yokohama, Japan. ACM, New York, NY, USA, 21 pages. https://doi.org/10.1145/3411764.3445312Google ScholarDigital Library
- Dominique Knutsen, Ludovic Le Bigot, and Christine Ros. 2017. Explicit feedback from users attenuates memory biases in human-system dialogue. International Journal of Human-Computer Studies 97: 77–87. https://doi.org/10.1016/j.ijhcs.2016.09.004Google ScholarCross Ref
- Ludovic Le Bigot, Eric Jamet, Jean-François Rouet, and Virginie Amiel. 2006. Mode and modal transfer effects on performance and discourse organization with an information retrieval dialogue system in natural language. Computers in Human Behavior 22, 3: 467–500. https://doi.org/10.1016/j.chb.2004.10.006Google ScholarDigital Library
- Oliver Lemon, "Conversational Interfaces", in Data-driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces, Springer, 2012. https://doi.org/10.1007/978-1-4614-4803-7Google ScholarCross Ref
- Zeming Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu. 2020. Towards Conversational Recommendation over Multi-Type Dialogs. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL’20), pages 1036–1049. http://dx.doi.org/10.18653/v1/2020.acl-main.98Google ScholarCross Ref
- Ewa Luger and Abigail Sellen. 2016. “Like Having a Really Bad PA”: The Gulf between User Expectation and Experience of Conversational Agents. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 5286–5297. https://doi.org/10.1145/2858036.2858288Google ScholarDigital Library
- David Maulsby, Saul Greenberg, and Richard Mander. 1993. Prototyping an intelligent agent through Wizard-of-Oz. In Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’93, 277–284. https://doi.org/10.1145/169059.169215Google ScholarDigital Library
- Sarah McRoberts, Joshua Wissbroecker, Ruotong Wang and F. Maxwell Harper. Exploring Interactions with Voice-Controlled TV. May 2019. https://doi.org/10.48550/arXiv.1905.05851Google Scholar
- Miroslav Melichar and Pavel Cenek. 2006. From vocal to multimodal dialogue management. In Proceedings of the 8th international conference on Multimodal interfaces - ICMI ’06, 59. https://doi.org/10.1145/1180995.1181008Google ScholarDigital Library
- Sebastian Moller, Klaus-Peter Engelbrecht, Christine Kuhnel, Ina Wechsung, and Benjamin Weiss. 2009. A taxonomy of quality of service and Quality of Experience of multimodal human-machine interaction. In 2009 International Workshop on Quality of Multimedia Experience, 7–12. https://doi.org/10.1109/QOMEX.2009.5246986Google ScholarCross Ref
- Cosmin Munteanu, Ben Cowan, Keisuke Nakamura, Pourang Irani, Sharon Oviatt, Matthew Aylett, Gerald Penn, Shimei Pan, Nikhil Sharma, Frank Rudzicz, and Randy Gomez. 2017. Designing Speech, Acoustic and Multimodal Interactions. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA ’17, 601–608. https://doi.org/10.1145/3027063.3027086Google ScholarDigital Library
- Cosmin Munteanu and Gerald Penn. 2014. Speech-based interaction: myths, challenges, and opportunities. In Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems - CHI EA ’14, 1035–1036. https://doi.org/10.1145/2559206.2567826Google ScholarDigital Library
- Christine Murad and Cosmin Munteanu. 2019. "I don't know what you're talking about, HALexa": the case for voice user interface guidelines. In Proceedings of the 1st International Conference on Conversational User Interfaces (CUI '19). Association for Computing Machinery, New York, NY, USA, Article 9, 1–3. https://doi.org/10.1145/3342775.3342795Google ScholarDigital Library
- Chelsea Myers, Anushay Furqan, Jessica Nebolsky, Karina Caro and Jichen Zhu. Patterns for How Users Overcome Obstacles in Voice User Interfaces. In ACM CHI Conference on Human Factors in Computing Systems, CHI 2018. https://doi.org/10.1145/3173574.3173580Google ScholarDigital Library
- Cathy Pearl. 2016. Designing Voice User Interfaces: Principles of Conversational Experiences. " O'Reilly Media, Inc. ISBN: 9781491955413Google Scholar
- Filip Radlinski and Nick Craswell. 2017. A Theoretical Framework for Conversational Search. In Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval (CHIIR '17). Association for Computing Machinery, New York, NY, USA, 117–126. https://doi.org/10.1145/3020165.3020183Google ScholarDigital Library
- Pareti, Silvia, and Tatiana Lando. "Dialog intent structure: A hierarchical schema of linked dialog acts." In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). 2018.Google Scholar
- Marta Perez Garcia, Sarita Saffon Lopez, and Hector Donis. 2018. Everybody is talking about Virtual Assistants, but how are people really using them? https://doi.org/10.14236/ewic/HCI2018.96Google Scholar
- Martin Porcheron, Joel E. Fischer, and Sarah Sharples. 2017. "Do Animals Have Accents?": Talking with Agents in Multi-Party Conversation. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). ACM, New York, NY, USA, 207-219. https://doi.org/10.1145/2998181.2998298Google ScholarDigital Library
- Martin Porcheron, Joel E. Fischer, Stuart Reeves, and Sarah Sharples. 2018. Voice Interfaces in Everyday Life. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). Association for Computing Machinery, New York, NY, USA, Paper 640, 1–12. https://doi.org/10.1145/3173574.3174214Google ScholarDigital Library
- Pernilla Qvarfordt, Arne Jönsson, and Nils Dahlbäck. 2003. The role of spoken feedback in experiencing multimodal interfaces as human-like. In Proceedings of the 5th international conference on Multimodal interfaces - ICMI ’03, 250. https://doi.org/10.1145/958432.958478Google ScholarDigital Library
- Filip Radlinski, Krisztian Balog, Bill Byrne and Karthik Krishnamoorthi. Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences. In Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, SIGdial 2019.Google ScholarCross Ref
- Dimitrios Rafailidis and Yannis Manolopoulos. 2019. Can Virtual Assistants Produce Recommendations? In Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics (WIMS2019). Association for Computing Machinery, New York, NY, USA, Article 4, 1–6. https://doi.org/10.1145/3326467.3326468Google ScholarDigital Library
- Chinnadhurai Sankar, Sandeep Subramanian, Christopher Pal, Sarath Chandar, and Yoshua Bengio. 2019. Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. arXiv:1906.01603 [cs]. Retrieved February 21, 2020 from http://arxiv.org/abs/1906.01603Google Scholar
- Bernhard Suhm, Brad Myers, and Alex Waibel. 2001. Multimodal error correction for speech user interfaces. ACM Transactions on Computer-Human Interaction 8, 1: 60–98. https://doi.org/10.1145/371127.371166Google ScholarDigital Library
- Yueming Sun and Yi Zhang. 2018. Conversational Recommender System. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. Association for Computing Machinery, New York, NY, USA, 235–244. https://doi.org/10.1145/3209978.3210002Google ScholarDigital Library
- Paul Thomas, Bodo Billerbeck, Nick Craswell, and Ryen W. White. 2019. Investigating Searchers’ Mental Models to Inform Search Explanations. ACM Trans. Inf. Syst. 38, 1, Article 10 (December 2019), 25 pages. https://doi.org/10.1145/3371390Google ScholarDigital Library
- Thomas, Paul and Czerwinski, Mary and McDuff, Daniel and Craswell, Nick. Theories of conversation for conversational IR. International Workshop on Conversational Approaches to Information Retrieval. 2020. https://www.microsoft.com/en-us/research/publication/theories-of-conversation-for-conversational-ir/Google Scholar
- Paul Thomas, Daniel McDuff, Mary Czerwinski, and Nick Craswell. 2020. Expressions of Style in Information Seeking Conversation with an Agent. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '20). Association for Computing Machinery, New York, NY, USA, 1171–1180. https://doi.org/10.1145/3397271.3401127Google ScholarDigital Library
- James Simpson. 2020. Are CUIs Just GUIs with Speech Bubbles? In Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20). Association for Computing Machinery, New York, NY, USA, Article 23, 1–3. https://doi.org/10.1145/3405755.3406143Google ScholarDigital Library
- Johanne R. Trippas, Damiano Spina, Lawrence Cavedon, Hideo Joho, and Mark Sanderson. 2018. Informing the Design of Spoken Conversational Search: Perspective Paper. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval (CHIIR '18). Association for Computing Machinery, New York, NY, USA, 32–41. https://doi.org/10.1145/3176349.3176387Google ScholarDigital Library
- Johanne R. Trippas, Damiano Spina, Paul Thomas, Mark Sanderson, Hideo Joho, and Lawrence Cavedon. 2020. Towards a model for spoken conversational search. Inf. Process. Manage. 57, 2 (Mar 2020). https://doi.org/10.1016/j.ipm.2019.102162Google ScholarDigital Library
- Sergej Truschin, Michael Schermann, Suparna Goswami, and Helmut Krcmar. 2014. Designing interfaces for multiple-goal environments: Experimental insights from in-vehicle speech interfaces. ACM Transactions on Computer-Human Interaction 21, 1: 1–24. https://doi.org/10.1145/2544066Google ScholarDigital Library
- Wataru Tsukahara and Nigel Ward. 2001. Responding to subtle, fleeting changes in the user's internal state. In Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’01, 77–84. https://doi.org/10.1145/365024.365047Google ScholarDigital Library
- Sruthi Viswanathan, Fabien Guillot, and Antonietta Maria Grasso. 2020. What is Natural? Challenges and Opportunities for Conversational Recommender Systems. In Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20). Association for Computing Machinery, New York, NY, USA, Article 40, 1–4. https://doi.org/10.1145/3405755.3406174Google ScholarDigital Library
- Marilyn A. Walker, Jeanne Fromer, Giuseppe Di Fabbrizio, Craig Mestel, and Don Hindle. 1998. What can I say?: evaluating a spoken language interface to Email. In Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’98, 582–589. https://doi.org/10.1145/274644.274722Google ScholarDigital Library
- Philip Weber and Thomas Ludwig. 2020. (Non-)Interacting with conversational agents: perceptions and motivations of using chatbots and voice assistants. In Proceedings of the Conference on Mensch und Computer (MuC '20). Association for Computing Machinery, New York, NY, USA, 321–331. https://doi.org/10.1145/3404983.3405513Google ScholarDigital Library
- J. Wilkie, M.A. Jack, and P.J. Littlewood. 2005. System-initiated digressive proposals in automated human–computer telephone dialogues: the use of contrasting politeness strategies. International Journal of Human-Computer Studies62, 1: 41–71. https://doi.org/10.1016/j.ijhcs.2004.08.001Google ScholarDigital Library
- Alexandra Vtyurina, Denis Savenkov, Eugene Agichtein, and Charles L. A. Clarke. 2017. Exploring Conversational Search With Humans, Assistants, and Wizards. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '17). Association for Computing Machinery, New York, NY, USA, 2187–2193. https://doi.org/10.1145/3027063.3053175Google ScholarDigital Library
- Xi Yang, Marco Aurisicchio, and Weston Baxter. 2019. Understanding Affective Experiences with Conversational Agents. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19, 1–12. https://doi.org/10.1145/3290605.3300772Google ScholarDigital Library
- Dounia Lahoual and Myriam Frejus. 2019. When Users Assist the Voice Assistants: From Supervision to Failure Resolution. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems - CHI EA ’19, 1–8. https://doi.org/10.1145/3290607.3299053Google ScholarDigital Library
- Clifford Nass and Kwan Min Lee. 2000. Does computer-generated speech manifest personality? an experimental test of similarity-attraction. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems (CHI ’00). Association for Computing Machinery, New York, NY, USA, 329–336. https://doi.org/10.1145/332040.332452Google ScholarDigital Library
- Kwan Min Lee and Clifford Nass. 2003. Designing social presence of social actors in human computer interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '03). Association for Computing Machinery, New York, NY, USA, 289–296. https://doi.org/10.1145/642611.642662.Google ScholarDigital Library
- Fedelucio Narducci, Pierpaolo Basile, Marco de Gemmis, Pasquale Lops & Giovanni Semeraro. An investigation on the user interaction modes of conversational recommender systems for the music domain. 2020. User Modeling and User-Adapted Interaction , volume 30, pages251–284. https://doi.org/10.1007/s11257-019-09250-7Google ScholarDigital Library
- Ma, Xiao, and Ariel Liu. "Challenges in Supporting Exploratory Search through Voice Assistants." arXiv preprint arXiv:2003.02986 (2020) https://doi.org/10.48550/arXiv.2003.02986.Google Scholar
- Yankelovich, N., Levow, G.-A., & Marx, M. (1995). Designing SpeechActs: Issues in Speech User Interfaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 369–376). New York, NY, USA: ACM Press/Addison-Wesley Publishing Co. https://doi.org/10.1145/223904.223952.Google ScholarDigital Library
- Andrea Iovine, Fedelucio Narducci, Giovanni Semeraro. 2020. Conversational Recommender Systems and natural language:: A study through the ConveRSE framework. Decision Support Systems, Volume 131, (2020). https://doi.org/10.1016/j.dss.2020.113250Google ScholarDigital Library
- Sebastian Zepf, Arijit Gupta, Jan-Peter Krämer, and Wolfgang Minker. 2020. EmpathicSDS: Investigating Lexical and Acoustic Mimicry to Improve Perceived Empathy in Speech Dialogue Systems. In Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20). Association for Computing Machinery, New York, NY, USA, Article 2, 1–9. https://doi.org/10.1145/3405755.3406125Google ScholarDigital Library
- Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft. 2018. Towards Conversational Search and Recommendation: System Ask, User Respond. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). Association for Computing Machinery, New York, NY, USA, 177–186. https://doi.org/10.1145/3269206.3271776Google ScholarDigital Library
- Zheng Zhang, Ryuichi Takanobu, Qi Zhu, Minlie Huang & Xiaoyan Zhu, Recent Advances and Challenges in Task-oriented Dialog Systems, Science China/ Technologic Science, 2020 (https://arxiv.org/pdf/2003.07490.pdf)Google ScholarCross Ref
- HTML5. Retrieved 24 February 2021 from https://html.spec.whatwg.org/Google Scholar
- JavaScript (Vue.js framework) Retrieved 24 February 2021 from https://developer.mozilla.org/en-US/docs/Web/JavaScriptGoogle Scholar
- WebSocket messaging protocol. Retrieved 24 February 2021 from https://html.spec.whatwg.org/multipage/web-sockets.htmlGoogle Scholar
- Mozilla DeepSpeech v0.8.2. Retrieved 24 February 2021 from https://github.com/mozilla/DeepSpeechGoogle Scholar
- Fisher. Retrieved 24 February 2021 from https://pdfs.semanticscholar.org/a723/97679079439b075de815553c7b687ccfa886.pdfGoogle Scholar
- LibriSpeech. Retrieved 24 February 2021 from http://www.danielpovey.com/files/2015_icassp_librispeech.pdfGoogle Scholar
- Switchboard. Retrieved 24 February 2021 from http://ieeexplore.ieee.org/document/225858/Google Scholar
- Common Voice English. Retrieved 24 February 2021 from https://voice.mozilla.org/datasetsGoogle Scholar
- MozillaTTS Retrieved 24 February 2021 from https://github.com/mozilla/TTSGoogle Scholar
- Tacotron2. Retrieved 24 February 2021 from https://arxiv.org/abs/1712.05884Google Scholar
- LJSpeech dataset. Retrieved 24 February 2021 from https://keithito.com/LJ-Speech-Dataset/Google Scholar
- TripAdvisor. Retrieved 24 February 2021 from https://www.tripadvisor.comGoogle Scholar
- Yelp Retrieved 24 February 2021 from https://www.yelp.comGoogle Scholar
- User Interviews. Retrieved 24 February 2021 from www.userinterviews.com/Google Scholar
- Rui Zhang, Stephen North, and Eleftherios Koutsofios. 2010. A comparison of speech and GUI input for navigation in complex visualizations on mobile devices. In Proceedings of the 12th international conference on Human computer interaction with mobile devices and services (MobileHCI '10). Association for Computing Machinery, New York, NY, USA, 357–360. https://doi.org/10.1145/1851600.1851665Google ScholarDigital Library
- Zoom. Retrieved 24 February 2021 from https://www.zoom.usGoogle Scholar
- World Health Organisation. Coronavirus disease (COVID-19) pandemic. 2020. Retrieved February 24, 2021 from < https://www.who.int/emergencies/diseases/novel-coronavirus-2019>Google Scholar
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