The exploration of computational techniques to learn, understand and produce human language content.
Natural language processing is concerned with the exploration of computational techniques to learn, understand and produce human language content.
Natural language processing technologies can assist both human-human communication (for example, machine translation) and human-machine communication (for example, conversational interfaces and automated personal assistants), and can analyse and learn from the vast amount of textual data available online.
Natural language processing is important to the development of intelligent interfaces, to explainable artificial intelligence (AI), and to data science. This strategy notes the opportunities for increased activity and for maintaining our capability in mainstream statistical natural language processing within UK academia.
In parallel with a focus on data science and intelligent interfaces, we aim to maintain mainstream statistical natural language processing capability.
Development of new intelligent interfaces
We aim to have a research and training portfolio that contributes to development of new intelligent interfaces with natural language processing at their core.
Natural language processing will increasingly serve as an interface for communicating between humans and systems (for example, in the ‘internet of things’) and dialogue management will become increasingly important, linking natural language processing with the related fields of speech technologies and human-robot interaction.
Researchers should also be encouraged to address challenges in multi-modal interfaces (for example, by exploring and exploiting the links between language and vision).
Extracting knowledge from textual data
We aim to have a portfolio of research and training that includes work on enabling extraction of knowledge from large-scale textual data. The opportunity exists for researchers to target interdisciplinary work in this area, such as textual analytics enabling analysis of medical records.
Computing with meaning
We aim to have researchers working towards the goal of computing with meaning, contributing to the broad objective in AI of developing computational methods for ascribing semantics to human behaviours – for example, natural human interaction.
Highly skilled people
We will aim to have a supply of people with high-level skills, reflecting increasingly acute demand as natural language processing technologies are used in an increasing number of applications.
Researchers have the opportunity to play an important role in delivering the objectives of EPSRC’s Future Intelligent Technologies and Data-enabled Decision-making cross-ICT priorities, and are well-placed to contribute to the other cross-ICT priorities.
To maximise impact, they should ensure effective communication with researchers in areas such as AI Technologies, Graphics and Visualisation and Human-Computer Interaction.
Responsible innovation is a significant consideration. Researchers are encouraged to address issues of trust, identity and privacy with regard to how natural language processing is used in social contexts and large-scale social networks.