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PhD in Computing Science: Moodagent - Conversational Music Assistant

  • Full or part time
  • Application Deadline
    Sunday, June 30, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Conversational AI interfaces are beginning to allow people to communicate naturally with computers for the first time. This PhD, in partnership with Moodagent, focuses on intelligent music agents. At a basic level, this involves research and development of task-based music agents to allow people to interact with music (playing music, creating playlists, searching for music, etc…). Further, the goal is the development of an ‘intelligent’ agent that can incorporate contextual recommendations (music for running, music for a beach party, etc…) in a conversational context. For example, the context may include multiple users interacting (to create a playlist for a party) and the agent may help mediate the interactions.

Going deeper, the aim is to develop conversational music intelligence that allows an agent to not simply perform tasks, but to converse with an agent about music. Music is a personal and subjective topic that is often vaguely defined, which make conversation in this domain both natural as well as an important research challenge. The explanatory descriptions from conversations about music will be used to explore research on deeper language-based understanding of music in order to improve quality and explainability of music retrieval and recommendation systems. This PhD will explore conversational music interactions in a cross-cultural and multilingual environment with Moodagent users in Denmark and India and will study key differences for this new and emerging group of users.

The PhD will study state-of-the-art task-based agent systems, including those based on deep learning models and that utilize reinforcement (and transfer) learning to learn agent policies. The research will also cover knowledge representation and research on construction of subjective personal knowledge graphs from conversation. It will incorporate conversational recommendation in multi-dimensional contexts, including social context, possibly involving groups of users.

The ideal candidate will have:
● A strong first degree in Computer Science or related discipline
● An interest in conversational artificial intelligence -- including machine learning (including reinforcement learning and structured prediction), information retrieval, and natural language understanding.
● Ideally the candidate has an interest in music
● An understanding of research principles and methods, through an undergraduate or postgraduate dissertation project.

Funding Notes

Funding is available to cover tuition fees for UK/EU applicant for 3.5 years, as well as paying a stipend at the Research Council rate (estimated £14,999 for Session 2019-20).

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