Using pupillometry to measure the cognitive load of synthetic speech

It is common to evaluate synthetic speech using listening tests in which intelligibility is measured by asking listeners to transcribe the words heard, and naturalness is measured using Mean Opinion Scores. But, for real-world applications of synthetic speech, the effort (cognitive load) required to understand the synthetic speech may be a more appropriate measure. Cognitive load has been investigated in the past, when rule-based speech synthesizers were popular, but there is little or no recent work using state-of-the-art text-to-speech. Studies on the understanding of natural speech have shown that the pupil dilates when increased mental effort is exerted to perform a task. We use pupillometry to measure the cognitive load of synthetic speech submitted to two of the Blizzard Challenge evaluations. Our results show that pupil dilation is sensitive to the quality of synthetic speech. In all cases, synthetic speech imposes a higher cognitive load than natural speech. Pupillometry is therefore proposed as a sensitive measure that can be used to evaluate synthetic speech