Srinivasan Janarthanam
Biographic Data
| ID | 5123723 |
|---|---|
| NAME | Srinivasan Janarthanam |
| GIVEN NAMES | Srinivasan |
| FAMILY NAME | Janarthanam |
| SIGNATURE | JANARTHANAM S |
| AFFILIATIONS | Heriot-Watt University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 6 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2016 |
| H-INDEX | 1 |
How expressiveness of a robotic tutor is perceived by children in a learning environment
We present a study investigating the expressiveness of two different types of robots in a tutoring task. The robots used were i) the EMYS robot, with facial expression capabilities, and ii) the NAO robot, without facial expressions but able to perform expressive gestures. Preliminary results show that the NAO robot was perceived to be more friendly, pleasant and empathic than the EMYS robot as a tutor in a learning environment
Adaptive Generation in Dialogue Systems Using Dynamic User Modeling
We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can learn to choose referring expressions to refer to domain entities for users with different levels of domain expertise, and whose domain knowledge is initially unknown to the system. We approach this problem using a three step process: collecting data …
How expressiveness of a robotic tutor is perceived by children in a learning environment
We present a study investigating the expressiveness of two different types of robots in a tutoring task. The robots used were i) the EMYS robot, with facial expression capabilities, and ii) the NAO robot, without facial expressions but able to perform expressive gestures. Preliminary results show that the NAO robot was perceived to be more friendly, pleasant and empathic than the EMYS robot as a tutor in a learning environment
Adaptive Generation in Dialogue Systems Using Dynamic User Modeling
We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can learn to choose referring expressions to refer to domain entities for users with different levels of domain expertise, and whose domain knowledge is initially unknown to the system. We approach this problem using a three step process: collecting data …
Adaptive Generation in Dialogue Systems Using Dynamic User Modeling
We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can learn to choose referring expressions to refer to domain entities for users with different levels of domain expertise, and whose domain knowledge is initially unknown to the system. We approach this problem using a three step process: collecting data …
How expressiveness of a robotic tutor is perceived by children in a learning environment
We present a study investigating the expressiveness of two different types of robots in a tutoring task. The robots used were i) the EMYS robot, with facial expression capabilities, and ii) the NAO robot, without facial expressions but able to perform expressive gestures. Preliminary results show that the NAO robot was perceived to be more friendly, pleasant and empathic than the EMYS robot as a tutor in a learning environment
AI in Service Interactions (2 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Human–computer interaction (2 works) · Adaptation (eye (1 works) · Baseline (sea (1 works) · Context (archaeology (1 works) · Conversation (1 works) · Domain (mathematical analysis (1 works) · Domain knowledge (1 works)