Publications

The L2TOR project generated over 160 publications, all listed here. The key publications describing the scientific and technological results of the project are:

Belpaeme, T., Baxter, P.E., Read, R., Wood, R., Cuayáhuitl, H., Kiefer, B., Racioppa, S., Kruijff-Korbayová, I., Athanasopoulos, G., Enescu, V., Looije, R., Neerincx, M., Demiris, Y., Ros-Espinoza, R., Beck, A., Cañamero, L., Hiolle, A., Lewis, M., Baroni, I., Nalin, M., Cosi, P., Paci, G., Tesser, F., Sommavilla, G., and Humbert, R. (2012). Multimodal child-robot interaction: Building social bonds. Journal of Human-Robot Interaction1(2), 33-53. Download full pdf.

Coninx, A., Baxter, P., Oleari, E., Bellini, S., Bierman, B., Blanson Henkemans, O., … & Hiolle, A. (2016). Towards long-term social child-robot interaction: using multi-activity switching to engage young users. Journal of Human-Robot Interaction5(1). Download full pdf.

Full publication list

  1. Athanasopoulos, G. & Verhelst, W (2013). A Phase-Modified Approach for TDE-Based Acoustic Localization. In Proceedings of the 14th Annual Conference of the International Speech Communication Association (Interspeech 2013), pages pp.2890 – 2894.
  2. Athanasopoulos, G., Brouckxon, H. & Verhelst, W (2012). Sound Source Localization for Real-World Humanoid Robots. In Proceedings of the 11th International Conference on Signal Processing (SIP 2012), pages 131 – 136. WSEAS.
  3. Athanasopoulos, G., Dekens, T. & Verhelst, W (2013). Acoustic Localization Enhanced with Phase Information from Modified STFT Magnitude. In Proceedings of the 18th International Conference on Digital Signal Processing.
  4. Athanasopoulos, G., Dekens, T., Brouckxon, H. & Verhelst, W (2012). The Effect of Speech Denoising Algorithms on Sound Source Localization for Humanoid Robots. In Proceedings of the 11th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA 2012), pages 369 – 374.
  5. Athanasopoulos, G., Wang, W., Wang, F., Yilmazyildiz, S., Oveneke, C., Enescu, V. et al (2012). Towards Autonomous Child-Robot Interaction. In 5th International Workshop on Human-Friendly Robotics.
  6. Baroni, I., Nalin, M., Baxter, P., Pozzi, C., Oleari, E., Sanna, A. et al (2014). What a Robotic Companion Could Do for a Diabetic Child. In 23rd IEEE International Conference on Robot and Human Interactive Communication (RoMAN 2014).
  7. Baroni, I., Nalin, M., Zelati, M. C., Oleari, E. & Sanna, A (2014). Designing motivational robot: How robots might motivate children to eat fruits and vegetables. In ROMAN 2014 conference.
  8. Baxter, P. & Belpaeme, T (2014). Pervasive Memory: the Future of Long-Term Social HRI Lies in the Past. In 3rd International Symposium on New Frontiers in Human-Robot Interaction at AISB’14, London.
  9. Baxter, P. & Browne, W (2010). Memory as the substrate of cognition: a developmental cognitive robotics perspective. In Johansson, B. & Balkenius, C. (editors), Proceedings of the Tenth International Conference on Epigenetic Robotics 2010.
  10. Baxter, P. & Trafton, G (2014). Cognitive Architectures for Human-Robot Interaction. In Proceedings of the 9th ACM/IEEE International Conference on Human-Robot Interaction, pages pp504-505.
  11. Baxter, P., Baroni, I., Nalin, M., Sanna, A. & Belpaeme, T (2013). Touchscreens as Mediators for Social Human-Robot Interactions: A Focus Group Evaluation involving Diabetic Children. In Collaboration meets Interactive Surfaces Workshop at ITS’2013.
  12. Baxter, P., Belpaeme, T., Cañamero, L., Cosi, P., Demiris, Y. & Enescu, V (2011). Long-Term Human-Robot Interaction with Young Users. In IEEE/ACM Human-Robot Interaction 2011 Conference (Robots with Children Workshop).
  13. Baxter, P., Cuayahuitl, H., Wood, R., Kruijff-Korbayova, I. & Belpaeme, T (2012). Towards Augmenting Dialogue Strategy Management with Multimodal Sub-Symbolic Context. In KI 2012, pages Poster.
  14. Baxter, P., de Greeff, J. & Belpaeme, T (2013a). Do children behave differently with a social robot if with peers?. In International Conference on Social Robotics (ICSR 2013).
  15. Baxter, P., de Greeff, J. & Belpaeme, T. (2013b). Cognitive Architecture for Human-Robot Interaction: Towards Behavioural Alignment. Journal of Biologically Inspired Cognitive Architectures6, pp30-39.
  16. Baxter, P., de Greeff, J., Wood, R. & Belpaeme, T (2012). ’And what is a Seasnake?’: Modelling the Acquisition of Concept Prototypes in a Developmental Framework. In International Conference on Development and Learning and Epigenetic Robotics, San Diego (USA), pages In press.
  17. Baxter, P., de Greeff, J., Wood, R. & Belpaeme, T. (2012). Modelling Concept Prototype Competencies using a Developmental Memory Model. Paladyn Journal of Behavioral RoboticsSpecial Issue on Advances in D.
  18. Baxter, P., Kennedy, J., Vollmer, A.-L., de Greeff, J. & Belpaeme, T (2014). Tracking gaze over time in HRI as a Proxy for Engagement and Attribution of Social Agency. In HRI’14, Late-Breaking Report, Bielefeld.
  19. Baxter, P., Wood, R. & Belpaeme, T (2010). Episodic Memory for Social Interaction. In Workshop on Synthetic Neuroethology, University of Sussex, pages Poster.
  20. Baxter, P., Wood, R. & Belpaeme, T (2012). A Touchscreen-Based ‘Sandtray’ to Facilitate, Mediate and Contextualise Human-Robot Social Interaction. In HRI’12, in press. Boston, MA, U.S.A.
  21. Baxter, P., Wood, R., Baroni, I., Kennedy, J., Nalin, M. & Belpaeme, T (2013). Emergence of Turn-taking in Unstructured Child-Robot Interactions. In Human Robot Interaction (HRI) 2013, Japan.
  22. Baxter, P., Wood, R., Belpaeme, T. & Nalin, M (2011). On Memory Systems for Companion Robots: Implementation Methodologies and Legal Implications. In AISB Symposium on Human Memory for Artificial Agents.
  23. Baxter, P., Wood, R., Morse, A. & Belpaeme, T (2011). Memory-Centred Architectures: Perspectives on Human-level Cognitive. In Proceedings of the Advances in Cognitive Systems tracks at the AAAI Fall Symposium 2011, pages 26-33. AAAI Press.
  24. Beck, A., Cañamero, L. & Bard, K (2010). Towards an affect space for robots to display emotional body language. In IREE RoMan Conference.
  25. Beck, A., Cañamero, L., Damiano, L., Sommavilla, G., Tesser, F. & Cosi, P (2011). Children Interpretation of Emotional Body Language Displayed by a Robot. In ICSR 2011.
  26. Beck, A., Cañamero, L., Hiolle, A., Damiano, L., Cosi, P., Tesser, F. et al (2013). Interpretation of Emotional Body Language Displayed by a Humanoid Robot: A Case Study with Children. In Special Issue on ICSR2011 of the International Journal of Social Robotics. Springer.
  27. Beck, A., Hiolle, A. & Cañamero, L (2013). Using Perlin Noise to Generate Emotional Expressions in a Robot. In Proceedings of CogSci 2013 (The 2013 Annual Meeting of the Cognitive Science Society.
  28. Beck, A., Hiolle, A., Mazel, A. & Cañamero, L (2010). Emotional body language displayed by Robots. In Affine 2010.
  29. Beck, A., Stevens, B., Bard, K. & Cañamero, L. (2012). Emotional Body Language Displayed by Artificial Agents. ACM transactions on Interactive Intelligent Systems. Special issue on Affective Interaction in Natural EnvironmentsArticle 2, p2:1-2:29,.
  30. Belpaeme, T. & Morse, A. (2010). Time will tell – why it is too early to worry. Interaction Studies11(2), 191-195.
  31. Belpaeme, T., Baxter, P., de Greeff, J., Kennedy, J., Read, R., Looije, R. et al (2013). Child-robot interaction: Perspectives and challenges. In Herrmann, G., Pearson, M., Lenz, A. et al (editors), Social Robotics, volume 8239 of Lecture Notes in Computer Science, pages 452-459. Springer International Publishing.
  32. Belpaeme, T., Baxter, P., Read, R., Wood, R., Cuayáhuitl, H., Kiefer, B. et al. (2013). Multimodal Child-Robot Interaction: Building Social Bonds. Journal of Human-Robot Interacion1(2), 33-53.
  33. Cai, L., Wang, F., Enescu, V. & Sahli, H (2014). Object segmentation based on Contour-Skeleton Duality. In 22nd International Conference on Patten Recognition (ICPR 2014). Stockholm, Sweden.
  34. Chatzis, S. & Demiris, Y. (2011). The Echo State Gaussian Process. IEEE Transactions on Neural Networks, .
  35. Chatzis, S. & Demiris, Y. (2012). The Infinite-Order Conditional Random Field Model for Sequential Data Modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence, .
  36. Chatzis, S. & Demiris, Y. (2012a). A Reservoir-Driven Non-Stationary Hidden Markov Model. Pattern Recognition journal, .
  37. Chatzis, S. P. & Demiris, Y. (2011). The Copula Echo State Network. Pattern Recognition Journal, .
  38. Chatzis, S. P. & Demiris, Y. (2012b). The Echo State Conditional Random Field Model for Sequential Data Modeling. Expert Systems with Applications, .
  39. Chatzis, S. P. & Demiris, Y. (2012c). A Sparse Nonparametric Hierarchical Bayesian Approach Towards Inductive Transfer for Preference Modeling,. Expert Systems With Applications, (doi: 10.10).
  40. Chatzis, S. P., Korkinof, D. & Demiris, Y (2011). The One-Hidden Layer Non-parametric Bayesian Kernel Machine. In 23rd IEEE International Conference on Tools with Artificial Intelligence, pages 825-831.
  41. Chatzis, S. P., Korkinof, D. & Demiris, Y. (2012a). A Quantum-Statistical Approach Toward Robot Learning by Demonstration. IEEE Transactions on Robotics, .
  42. Chatzis, S. P., Korkinof, D. & Demiris, Y. (2012b). A nonparametric Bayesian approach toward robot learning by demonstration,. Robotics and Autonomous Systems, .
  43. Cohen, I., Looije, R. & Neerincx, M (2011). Child’s recognition of emotions in robots’ face and body. In HRI 2011 Conference, pages Poster.
  44. Cohen, I., Looije, R. & Neerincx, M. (2014). Children’s Perception of Robot’s Emotions: Effects of Platform, Context and Experience. International Journal of Social Robotics.
  45. Cosi, P., Nicolao, M., Paci, G., Sommavilla, G. & Tesser, F (2014). Comparing open source ASR toolkits on italian children speech. In 4th Workshop on Child-Computer Interaction (WOCCI 2014) at INTERSPEECH. Singapore, Singapore.
  46. Cosi, P., Paci, G., Sommavilla, G., Tesser, F., Nalin, M. & Baroni, I (2012). An italian event-based ASR-TTS system for the nao robot. In In 7th Conference of the Italian Association of Speech Sciences “La voce nelle applicazioni”, pages 177–198.
  47. Cuayahuitl, H (2011). Learning Dialogue Agents with Bayesian Relational State Representations. In Proceedings of the IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems (IJCAI-KRPDS), Barcelona, Spain,, pages 9 – 15. ICAI.
  48. Cuayahuitl, H. & Dethelfs, N (2011). Optimizing Situated Dialogue Management in Unknown Environments. In INTERSPEECH 2011, pages 1009-1012.
  49. Cuayahuitl, H. & Dethlefs, N (2012). Dialogue Systems Using Online Learning: Beyond Empirical Methods. In In proceedings of the NAACL-HLT Workshop on Future Directions and Needs in the Spoken Dialog Community: Tools and Data.
  50. Cuayahuitl, H. & Dethlefs, N (2012). Hierarchical Multiagent Reinforcement Learning for Coordinating Verbal and Non-verbal Actions in Robots. In ECAI Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Language, Motor Control and Vision, pages 27-29.
  51. Cuayahuitl, H. & Kruijff-Korbayova, I (2011). Towards Learning Human-Robot Dialogue Policies Combining Speech and Visual Beliefs. In In proceedings of the Workshop on Paralinguistic Information and its Integration in Spoken Dialogue Systems, Granada, Spain, Sep 2011., pages 133-140. Springer.
  52. Cuayahuitl, H. & Kruijff-Korbayova, I (2012). An Interactive Humanoid Robot Exhibiting Flexible Sub-Dialogues. In Proceedings of The 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demo Session.
  53. Cuayahuitl, H., Frommberger, L., Dethlefs, N. & Sahli, H (2012). Bridging the Gap Between Language, Motor Control and Vision. In Proceedings of the ECAI Workshop on Machine Learning for Interactive Systems (MLIS):.
  54. Cuayahuitl, H., Kruijff-Korbayova, I. & Dethlefs, N (2012). Hierarchical Dialogue Policy Learning Using Flexible State Transitions and Linear Function Approximation. In International Conference on Computational Linguistics (COLING).
  55. Cuayahuitl, H., Kruijff-Korbayova, I. & Dethlefs, N (2014b). Non-Strict Hierarchical Reinforcement Learning for Interactive Systems and Robots. In ACM Transactions on Interactive Intelligent Systems.
  56. Cuayahuitl, H., Kruijff-Korbayova, I. & Dethlefs, N. (2014a). Non-Strict Hierarchical Reinforcement Learning for Interactive Systems and Robots. ACM Transactions on Interactive Intelligent Systems4(3), 1 – 25.
  57. Damiano, L. & Cañamero, L. (2012). The Frontier of Synthetic Knowledge. World Futures: Journal of General Evolution, (68), pp. 171-177.
  58. Damiano, L., Hiolle, A. & Cañamero, L (2011). Grounding Synthetic Knowledge: An epistemological framework and criteria of relevance for the scientific exploration of life, affect and social cognition. In ECAL 2011.
  59. de Greeff, J., Henkemans, O. B., Fraaije, A., Solms, L., Wigdor, N. & Bierman, B (2014). Child-Robot Interaction in the Wild: Field Testing Activities of the ALIZ-E Project. In Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction.
  60. de Greeff, J., Janssen, J. B., Looije, R., Mioch, T., Alpay, L., Neerincx, M. A. et al (2013). “Activity Switching in Child-Robot Interaction: a Hospital Case Study”. In ICSR2013.
  61. Dekens, T. & Verhelst, W (2011). On Noise Robust Activity Detection. In Interspeech 2011, pages 2649-2652.
  62. Dethelfs, N. & Cuayahuitl, H (2011). Hierarchical Reinforcement Learning and Hidden Markov Models for Task-Orientated Natural Language Generation. In In Proceedings of the Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT), Portland, OR, USA, Jun 2011, pages 654-659.
  63. Dethlefs, N. & Cuayahuitl, H (2012). Comparing HMMs and Bayesian Networks for Surface Realisation. In In proceedings of the National Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL-HLT).
  64. Dethlefs, N., Cuayahuitl, H. & Viethen, J (2011). Optimising Natural Language Generation Decision Making For Situated Dialogue. In In Proceedings of the Annual Meeting on Discourse and Dialogue (SIGDial), Portland, OR, USA,, pages 78 – 87.
  65. Egbert, M. & Barandiaran, X. (2014). Modelling habits as self-sustaining patterns of sensorimotor behavior. Frontiers in Human Neuroscience8(590), 1 – 15.
  66. Egbert, M. & Cañamero, L (2014). Habit-based Regulation of Essential Variables. In Accepted at the the 14th conference on the synthesis and simulation of living systems, ALIFE 14.
  67. Galata, V., Benin, A., Cosi, P., Leone, G. R., Paci, G., Sommavilla, G. et al (2014). Discovering the Italian Literature: Interactive Access to Audio-indexed Text Resources. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14).
  68. Gonzalez, I., Sahli, H. & Verhelst, W (2010). Automatic Recognition of Lower Facial Action Units. In 7th International Conference on Methods and Techniques in Behavioural Research, pages 204-207.
  69. Gonzalez, I., Sahli, H., Enescu, V. & Verhelst, W (2011). Context-Independent Facial Action Unit Recognition using Shape and Gabor Phase Information. In Proceedings of the International Conference on Affective Computing and Intelligent Interaction (ACII2011), Memphis, pages ACII (1) 2011: 548-5.
  70. Greeff, J. D., Baxter, P., Wood, R. & Belpaeme, T (2012). From Penguins to Parakeets: a developmental approach to modelling conceptual prototypes. In Postgraduate Conference on Robotics and Development of Cognition at ICANN 2012.
  71. Henkemans, O. A., Bierman, B. P., Janssen, J., Neerincx, M. A., Looije, R., van der Bosch, H. et al. (2013). Using a robot to personalise health education for children with diabetes type 1: A pilot study. Patient Education and Counseling, (PEC-4519), 8.
  72. Henkemans, O. A., Hoondert, V., Schrama-Groot, F., Looije, R., Alpay, L. L. & Neerincx, M. A. (2012). “I just have diabetes”: children’s need for diabetes self-management support and how a social robot can accommodate their needs. Patient Intelligence, .
  73. Hiolle, A., Cañamero, L., Andry, P., Blanchard, A. & Gaussier, P (2010). Using the interaction rhythm as a natural reinforcement signal for social robots: a matter of belief. In International Conference on Social Robotics, ICSR 2010.
  74. Hiolle, A., Cañamero, L., Davila-Ross, M. & Bard, K. A. (2012). Eliciting caregiving behavior in dyadic human-robot attachment-like interactions. ACM transactions on Interactive Intelligent Systems, .
  75. Hiolle, A., Lewis, M. & Cañamero, L (2014a). A Robot that Uses Arousal to Detect Learning Challenges and Seek Help. In Accepted at the 14th conference on the synthesis and simulation of living systems, ALIFE 14.
  76. Hiolle, A., Lewis, M. & Cañamero, L. (2014b). Arousal Regulation and Affective Adaptation to Human Responsiveness by a Robot that Explores and Learns a Novel Environment. Frontiers in Neurorobotics, (8).
  77. Janssen, J. B., van der Wal, C. C., Neerincx, M. A. & Looije, R (2011). Motivating children to learn arithmetic with an adaptive robot game. In ICSR Conference, pages 153-162.
  78. Jiang, D., Cui, Y., Zhang, X., Fan, P., Ganzalez, I. & Sahli, H (2011). Audio Visual Emotion Recognition Based on Triple-Stream Dynamic Bayesian Network Models. In Affective Computing and Intelligent Interaction, Lecture Notes in Computer Science. Springer Berlin / Heidelberg, ISBN-ISSN: 978-3-642-24599-2,.
  79. Kennedy, J., Baxter, P. & Belpaeme, T (2013). Constraining Content in Mediated Unstructured Social Interactions: Studies in the Wild. In 5th International Workshop on Affective Interaction in Natural Environments at ACII 2013.
  80. Kennedy, J., Baxter, P. & Belpaeme, T (2014). Children Comply with a Robot’s Indirect Requests. In Proceedings of the 9th ACM/IEEE International Conference on Human-Robot Interaction, Bielefeld.
  81. Kennedy, J., de Greeff, J., Read, R., Baxter, P. & Belpaeme, T (2014). The Chatbot Strikes Back. In Proceedings of the 9th ACM/IEEE International Conference on Human-Robot Interaction, Bielefeld, Germany, pages Poster.
  82. Kiefer, B. & Krieger, H.-U (2013). An Efficient Typed Feature Structure Index: Theory and Implementation. In Proceedings of the 13th International Conference on Parsing Technologies. International Conference on Parsing Technologies (IWPT-2013).
  83. Korkinof, D. & Demiris, Y (2013). Online Quantum Mixture Regression for Trajectory Learning by Demonstration. In International Conference on Intelligent Robot and Systems. Tokyo, Japan.
  84. Krieger, H.-U. & Kiefer, B (2011). Converting CCGs into Typed Feature Structure Gram- mars. In  of 18th Conference on Head-Driven Phrase Structure Grammar. Seattle, WA.
  85. Kruijff-Korbayova, I., Athanasopoulos, G., Beck, A., Cosi, P., Cuayahuitl, H., Dekens, T. et al (2011). An Event-Based Conversational System for the Nao Robot. In IWSDS2011 Workshop on Paralinguistic Information and its Integration in Spoken Dialogue Systems, pages 125-132. Springer.
  86. Kruijff-Korbayova, I., Cuay´ahuitl, H., Kiefer, B., Schr¨oder, M., Cosi, P., Paci, G. et al (2012). Spoken Language Processing in a Conversational System for Child-Robot Interaction. In Proceedings of WOCCI 2012 – Workshop on Child, Computer and Interaction Satellite Event of INTERSPEECH.
  87. Kruijff-Korbayova, I., Kiefer, B., Baroni, I. & Zelati, M. C (2013). Making Human-Robot Quiz Dialogue More Conversational by Adding Non-Quiz Talk. In The 17th Workshop on the Semantics and Pragmatics of Dialogue (DialDam), pages Poster.
  88. Kruijff-Korbayová, I., Kruijff, G. J. & Janicek, M (2011). Planning and Realizing Questions in Situated Human-Robot Interaction. In In Proceedings of the AAAI Fall Symposium on Question Generation.
  89. Kruijff-Korbayova, I., Oleari, E., Baroni, I., Kiefer, B., Zelati, M. C., Pozzi, C. et al (2014). Effects of Off-Activity Talk in Human-Robot Interaction with Diabetic Children. In Ro-Man 2014: The 23rd IEEE International Symposium on Robot and Human Interactive Communication.
  90. Latacz, L., Mattheyses, W. & Verhelst, W (2010). The VUB Blizzard Challenge 2010 Entry: Towards Automatic Voice Building. In Blizzard Challenge 2010.
  91. Latacz, L., Mattheyses, W. & Verhelst, W (2011). Joint Target and Join Cost Weight Training for Unit Selection Synthesis. In Interspeech 2011, pages 321-324.
  92. Latacz, L., Mattheyses, W. & Verhelst, W (2013). Speaker-Specific Pronunciation for Speech Synthesis. In Proceedings of the 16th International Conference on Text, Speech and Dialog (TSD 2013), pages pp. 501–508.
  93. Lee, K., Kim, T.-K. & Demiris, Y (2012). Learning Action Symbols for Hierarchical Grammar Induction. In Proceedings of the 21st International Conference on Pattern Recognition (ICPR),, pages pp. 3778-3782, IEEE.
  94. Lewis, M. & Cañamero, L (2013). Are Discrete Emotions Useful in Human-Robot Interaction? Feedback from Motion Capture Analysis. In In proceedings of the International Conference on Affective Computing and Intelligent Interaction.
  95. Lewis, M. & Cañamero, L (2014). An Affective Autonomous Robot Toddler to Support the Development of Self-Efficacy in Diabetic Children. In Accepted at the 23rd Annual IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2014).
  96. Lewis, M., Hiolle, A. & Cañamero, L (2014). Pleasure, Persistence and Opportunism in Action Selection. In Accepted at the the 14th conference on the synthesis and simulation of living systems, ALIFE 14.
  97. Li, L., Yong Zhao, ., Jiang, D., Zhang, Y., Wang, F., Gonzalez, I. et al (2013). Hybrid Deep Neural Network – Hidden Markov Model (DNN-HMM) Based Speech Emotion Recognition. In Humaine Association Conference on Affective Computing and Intelligent Interaction – ACII2013.
  98. Lison, P (2011). Multi-Policy Dialogue Management. In Sigdial 2011. Association for Computational Linguistics.
  99. Lison, P. & Kruijff, G.-J (2010). Policy Activation for Open-ended Dialogue Management. In AAAI Fall Symposium on Dialog with Robots (2010).
  100. Lones, J., Cañamero, L. & Lewis, M (2013). Epigenetic adaptation in action selection environments with temporal dynamics. In Advances in Artificial Life, ECAL 2013: Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems., pages pp. 505-512.
  101. Lones, J., Lewis, M. & Cañamero, L (2014). Hormonal modulation of development and behaviour permits a robot to adapt to novel interactions. In Accepted at the 14th conference on the synthesis and simulation of living systems, ALIFE 14.
  102. Looije, R., Neerincx, M. A. & Hindriks, K (2014). How to Design and Test Interactive Robots. In HRI 2014 Workshop Paper.
  103. Looije, R., van der Zalm, A., Neerincx, M. A. & Beun, R.-J (2012). Help, I need some body: The effect of embodiment on playful learning. In The 21st IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN2012), pages 718-724.
  104. Mattheyses, W., Latacz, L. & Verhelst, W (2011). Auditory and Photo-realistic Audiovisual Speech Synthesis for Dutch. In Proceedings of the International Conference on Auditory-Visual Speech Processing, AVSP2011, pages pp.53 – 58.
  105. Nalin, M., Baroni, I. & Sanna, A (2012). A Motivational Robot Companion for Children in Therapeutic Setting. In IROS 2012.
  106. Nalin, M., Baroni, I., Kruijff-Korbayova, I., Cañamero, L., Lewis, M., Beck, A. et al (2012). Children’s adaptation in multi-session interaction. In IEEE RO-MAN 2012.
  107. Nalin, M., Baroni, I., Sanna, A. & Pozzi, C (2012). Robotic Companion for Diabetic Children. In Conference Interaction Design for Children 2012.
  108. Nalin, M., Bergamini, L., Giusti, A., Baroni, I. & Sanna, A (2011). Children’s perception of a Robotic Companion in a mildly constrained setting. In IEEE/ACM Human-Robot Interaction 2011 Conference (Robots with Children Workshop).
  109. Neerincx, M. (2010). Social Robots for Self-management of Health-promoting Activities. CyberTherapy & Rehabilitation, , 3, 36-37.
  110. Nicolao, M. & Cosi, P (2011). Comparing SPHINX vs. SONIC in an Italian Children’s speech recognition system. In 7th Conference of the Italian Association of Speech Sciences.
  111. Nicolao, M., Tesser, F. & Moore, R. K (2013). A phonetic-contrast motivated adaptation to control the degree-of-articulation on Italian HMM-based synthetic voices. In 8th Speech Synthesis Workshop, pages 107–112.
  112. Oveneke, M. C., Enescu, V. & Sahli, H (2012). Real-time Dance Pattern Recognition Invariant to Anthropometric and Temporal Differences. In ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS (ACIVS 2012), pages 407-419. Springer.
  113. Paci, G., Sommavilla, G. & Cosi, P. (2012). Sad-based italian forced alignment strategies. Evaluation of Natural Language and Speech Tools for Italian, volume 7689 of Lecture Notes in Computer Science7689, 322–329.
  114. Pammi, S. & Schroder, M (2011). Evaluating the meaning of synthesized listener vocalizations. In Proceedings – Interspeech 2011.
  115. Pammi, S., Charfuelan, M. & Schroder, M (2010). Multilingual Voice Creation Toolkit for the MARY TTS Platform. In LREC 2010.
  116. Pammi, S., Schroder, M. & Charfuelan, M. (2011). Multidimensional meaning annotation of listener vocalizations for synthesis, Proceedings – Workshop Emotion and Computing, Berlin, Germany, Springer.
  117. Pammi, S., Schroder, M., Charfuelan, M., Turk, O. & Steiner, I (2010). Synthesis of listener vocalisations with imposed intonation contours. In Seventh ISCA Tutorial and Research Workshop on Speech Synthesis 2010.
  118. Read, R. & Belpaeme, T (2010). Interpreting non-linguistic utterances by robots: studying the influence of physical appearance. In Affine 2010 (3rd International Workshop on Affective Interaction in Natural Enviroments.
  119. Read, R. & Belpaeme, T (2012). How to Use Non-Linguistic Utterances to Convey Emotion in Child-Robot Interaction. In HRI’12, Boston USA.
  120. Read, R. & Belpaeme, T (2013a). Using the AffectButton to Measure Affect in Child and Adult-Robot Interaction. In Human Robot Interaction (HRI 2013).
  121. Read, R. & Belpaeme, T (2013b). People Interpret Robotic Non-Linguistic Utterances Categorically. In Human Robot Interaction (HRI 2013).
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  123. Read, R. & Belpaeme, T (2014b). Non-Linguistic Utterances Should be Used Alongside Language, Rather than on their Own or as a Replacement. In Proceedings of the 9th International Conference on Human-Robot Interaction (HRI’14).
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