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


Interacting with Global Content

How do Users Perceive Information: Analyzing User Feedback while Annotating Textual Units

  • Posted: 3 Nov 2017
  • Author: , Piyush Arora, Gareth J.F. Jones
  • Publication: SCST 2017 - Second Workshop on Supporting Complex Search Tasks @ CHIIR
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

Identifying Effective Translations for Cross-lingual Arabic-to-English User-generated Speech Search

  • Posted: 4 Mar 2017
  • Author: Andy Way, Haithem Afli, Ahmad Khwileh, Gareth J.F. Jones
  • Publication: WANLP 2017 - The Third Workshop on Arabic Natural Language proceeding, co-located with EACL 2017
Interacting with Global Content

  • Posted: 1 Jan 2018
  • Author: , Emma Carrigan, Ludovic Hoyet, Rachel McDonnell, Quentin Avril
  • Publication: EG 2018 - 39th Eurographics conference

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.

9 am
Come and join us @TLRHub for #LibTech showcase #LIBER2019 Tea/coffee, cakes and great demos on show!


Sign up to our newsletter for all the latest updates on ADAPT news, events and programmes.
Archived newsletters can be viewed here.