Detection of emotional states from speech and text

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing, and will be supervised by Dr Ella Haig and Dr Alaa Mohasseb.

The work on this project could involve:

• Processing voice signals for the detection of emotional states
• Processing text for the detection of emotional states, topics and other contextual information
• Combining the signal and text processing into a unified approach for improved emotional states detection 

Project description

As speech is increasingly used in our interactions with technology, this type of data is more readily available, giving researchers in academia and industry opportunities to extract useful information from this type of data with increased precision and to ultimately improve this technology. The voice and speech recognition market is due to grow significantly in the next few years, with high demand from consumers for voice-controlled smart devices.

This project aims to develop methods for detection of emotional states from speech and text (captured by voice-based technology) using machine learning, Natural Language Processing (NLP) and signal processing. The data from this project comes from Deary, a London-based company that aims to help people who care about memories by automatically capturing, organizing, and re-proposing the most meaningful conversations of their digital and real lives, through Artificial Intelligence technologies. 

Dr Ella Haig has over 15 years of research experience in modelling user behaviours/characteristics (including emotions) using artificial intelligence and machine learning techniques. Dr Alaa Mohasseb has research experience in the field of Text Mining, Natural Language Processing, and Machine learning.

This project will give you the opportunity to work on a cutting-edge research project, as well as collaborate with an industrial partner, thus giving you real-world experience. Moreover, you will be gaining skills in a high-demand area, which would benefit your employability prospects.

General admissions criteria

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

The successful candidate should have expertise in the fundamentals of data analytics and machine learning, good Python programming skills and knowledge of machine learning and deep learning frameworks (e.g. Scikit-Learn, TensorFlow and Keras).

Familiarity with audio signal processing (e.g. the pyAudioProcessing library) and with NLP libraries and utilities (e.g. NLTK, Spacy, Gensim) is desirable. 

How to Apply

We’d encourage you to contact Dr Ella Haig ([Email Address Removed]) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please quote project code COMP5850521 when applying.