Signal processing for multichannel audio

The PhD research will focus on algorithms to improve signals in audio systems where there are more than one channel, otherwise known as multichannel audio systems. Multichannel systems are in common use as they are vital to many enhancement algorithms for example removing background noise from conferencing calls. One problem that is being addressed is finding ways of reducing the amount of information that is needed to represent signals in multichannel systems. This could be useful in situations where there is a limited bandwidth to transmit many signals, where without this technology multichannel audio systems could not be used. Another problem is removing the effect of reverberation from microphone signals. De-reverberation reduces the performance of voice recognition software such as is commonly found in home assistants, therefore effective algorithms that remove the reverberation before the signal is sent to a voice recognition system are desirable. Another problem that may be addressed is the interpretation of machine learning methods. Algorithms that rely on machine learning are highly effective at tasks that are otherwise very difficult. However, there is a lack of interpretability, that is to say, an output is generated for a given input but it is very difficult for experts to say what is actually happening in machine learning algorithms. Some work may be conducted in finding ways of interpreting these systems when they are applied to signal processing. This would be beneficial in many cases for example it would allow researchers to understand and design better algorithms, and also means machine learning could be applied to safety critical applications with a greater understanding of the risks.


The main approach to conducting the research will be to use programming languages to simulate situations such as rooms etc. and implement the algorithms in simulations. This is the most widespread technique used in the field as it is often the simplest and most effective way of designing and assessing these algorithms.


The research could be categorised under with the following research areas:
Digital Signal Processing
Music and Acoustics Technology
Artificial intelligence Technologies
Speech Technology
Natural Language Processing