Interacting with Global Content

Interacting with Global Content

This research activity allows people to interact with digital content in ways that are more intuitive and that mimic the richness of human perception in all interaction. This research goes beyond text and speech-based exchange of content, to full multimodal interfaces that interpret information from a multitude of audio and visual cues. By furthering both the understanding and automatic analysis of human interaction with digital content and other humans, we are transforming the retrieval, understanding, and delivery of multimodal content for users.

In driving a more complete understanding of multimodal interaction between humans and for humans with digital content, we build automatic systems that track human engagement and affective response, and judge how best to retrieve and render responsive content for the user.

Research team

Publications

Conference Paper

The Influence of Synthetic Voice on the Evaluation of a Virtual Character

  • Posted: 20 Aug 2017
  • Author: João Cabral, Rachel McDonnell, Benjamin Cowan, Katja Zibrek
  • Publication: Interspeech 2017
Interacting with Global Content

Perception and prediction of speaker appeal - A single speaker study

  • Posted: 5 Jan 2018
  • Author: , Ailbhe Cullen, Andrew Hines, Naomi Harte
  • Publication: Computer Speech & Language
Interacting with Global Content

Forensic comparison of ageing voices from automatic and auditory perspectives

  • Posted: 1 Sep 2015
  • Author: Naomi Harte, Finnian Kelly
  • Publication: International Journal of Speech Language and the Law
Conference Paper

Perception & Perspective: An Analysis of Discourse and Situational Factors in Reference Frame Selection

  • Posted: 6 Mar 2019
  • Author: , Robert Ross, Kavita Thomas
  • Publication: DAP 2018 - Workshop on Dialogue and Perception

Research Goals

New methods are being developed to process both speech-only and audio-visual data, and train statistical engines to infer attentional state. The ability to track user engagement and interest in conversational interaction is key to reproducing natural interactions in the future, be that with a robot, personal assistant or avatar. The research explores what makes an avatar, or computer generated speaker, engaging to a user. The research uniquely combines ADAPT expertise on expressive synthesis, the role of paralinguistic cues in speech, and avatar animation.

Also addressed are issues of multimodal content relevant to interaction from two perspectives: The first addresses challenges of locating and isolating objects of interest in a visual stream and exploiting visual cues in speech to augment speech recognition capabilities. Learning techniques from unstructured multimodal data streams are also examined. The second is addressed by establishing methods for the exploitation of dialogue in user interaction in information retrieval, and to the exploitation of context to enable proactive information retrieval.

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