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2025
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Video
In this talk I examine the role of humanities research where nearly every aspect of human experience is turned into data and analysed, in many cases to model, predict and modify behaviour. As a result and through advances in computing technology, artificial intelligence systems have colonised traditional areas of humanities research, including linguistics and language studies. Today, large multimodal models (LMM) can process text, images, videos and sound, potentially leading to the development of algorithmic approaches to modelling society and culture. In this talk, I explore how humanities researchers can leverage the benefits and mitigate the risks of these latest technological developments and prepare scholars for the challenges which lie ahead. I provide some examples from the Digital Media and Society Institute (DMSI) at the University of Liverpool where communication and media researchers are working with data scientists to investigate how multimodal information is re-contextualised across online media platforms. This includes new methods for studying information distortions (e.g. misinformation, disinformation and memes) and public reactions to key events.
Event date: 31/03/2025
Speaker: Professor Kay O’HALLORAN (University of Liverpool)
Hosted by: Faculty of Humanities
- Keywords:
- Artificial intelligence Research Humanities -- Research
- Resource Type:
- Video
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Video
People are now regularly interacting with voice assistants (VAs), which are conversational agents that allow users to use spoken language to interface with a machine to complete tasks. The huge adoption and daily use of VAs by millions of people - and its increasing use for financial, healthcare, and educational applications - raises important questions about the linguistic and social factors that affect spoken language interactions with machines.
We are exploring issues of linguistic and social biases that impact speech communication in human-computer interaction - particularly during cross-language transfer, learning, or adaptation of some kind. In this talk, I will present two case studies illustrating some of our most recent work in this area. The first study looks at a case of cross-language ASR transfer. We find systematic linguistic and phonetic disparities in language transfer by machines trained on a source language to speech recognition of a novel target, low-resource language. The second study looks at a case of social bias in word learning by humans using voice-enabled apps. We find the word learning is inhibited when there are mismatching social cues presented by the voice and the linguistic information.
Together, along with highlights from other ongoing work in my lab, the aim of this talk is to underscore that human-computer linguistic communication is a rich testing ground for investigating issues in speech and language variation. Examining linguistic variation during HCI can enrich and elaborate linguistic theory, as well as present opportunities for linguists to provide insights for improving both the function and fairness of these technologies.
Event date: 25/03/2025
Speaker: Professor. Georgia ZELLOU (University of California, Davis)
Hosted by: Faculty of Humanities
- Subjects:
- Communication and Language and Languages
- Keywords:
- Linguistics English language -- Variation Speech processing systems English language -- Spoken English Human-computer interaction
- Resource Type:
- Video