Musical training as a potential tool for improving speech perception in background noise

Understanding speech in background noise is a complex and challenging task that causes difficulty for many people, including young children and older adults. Musicians, on the other hand, appear to have an enhanced ability to perceive speech in noise. This has prompted suggestions that musical training could help people who struggle to communicate in complex auditory environments. The experiments presented in this thesis were designed to investigate if and how musical training could be used as an intervention for improving speech perception in noise. The aim of Experiment 1 was to identify specific musical skills which could be targeted for training. Musical beat perception was found to be strongly correlated with speech perception in noise. It was hypothesised that musical beat perception might enhance speech perception in noise by facilitating temporal orienting of attention to important parts of the signal. Experiments 2, 3 and 4 investigated this hypothesis using a rhythmic priming paradigm. Musical rhythm sequences were used to prime temporal expectations, with performance for on-beat targets predicted to be better than that for temporally displaced targets. Rhythmic priming benefits were observed for detection of pure-tone targets in noise and for identification of words in noise. For more complex rhythms, the priming effect was correlated with musical beat perception. Experiment 5 used the metric structure within a sentence context to prime temporal expectations for a target word. There was a significant benefit of rhythmic priming for both children and adults, but the effect was smaller for children. In Experiment 6, a musical beat training programme was devised and evaluated for a group of older adults. After four weeks of training, a small improvement in speech reception thresholds was observed. It was concluded that beat perception is a useful skill to target in a musical intervention for speech perception in noise