Measuring the naturalness of synthetic speech

Even the highest quality synthetic speech generated by rule sounds unlike human speech. As the intelligibility of rule-based synthetic speech improves, and the number of applications for synthetic speech increases, the naturalness of synthetic speech will become an important factor in determining its use. In order to improve this aspect of the quality of synthetic speech it is necessary to have diagnostic tests that can measure naturalness. Currently, all of the available metrics for evaluating the acceptability of synthetic speech do not distinguish sufficiently between measuring overall acceptability (including naturalness) and simply measuring the ability of listeners to extract intelligible information from the signal. In this paper we propose a new methodology for measuring the naturalness of particular aspects of synthesized speech, independent of the intelligibility of the speech. Although naturalness is a multidimensional, subjective quality of speech, this methodology makes it possible to assess the separate contributions of prosodic, segmental, and source characteristics of the utterance. In two experiments, listeners reliably differentiated the naturalness of speech produced by two male talkers and two text-to-speech systems. Furthermore, they reliably differentiated between the two text-to-speech systems. The results of these experiments demonstrate that perception of naturalness is affected by information contained within the smallest part of speech, the glottal pulse, and by information contained within the prosodic structure of a syllable. These results show that this new methodology does provide a solid basis for measuring and diagnosing the naturalness of synthetic speech.