A global, boundary-centric framework for unit selection text-to-speech synthesis

The level of quality that can be achieved by modern concatenative text-to-speech synthesis heavily depends on the optimization criteria used in the unit selection process. While effective cost functions arise naturally for prosody assessment, the criteria typically selected to quantify discontinuities in the speech signal do not closely reflect users´ perception of the resulting acoustic waveform. This paper introduces an alternative feature extraction paradigm, which eschews general purpose Fourier analysis in favor of a modal decomposition separately optimized for each boundary region. The ensuing transform framework preserves, by construction, those properties of the waveform which are globally relevant to each concatenation considered. In addition, it leads to a novel discontinuity measure which jointly, albeit implicitly, accounts for both interframe incoherence and discrepancies in formant frequencies/bandwidths. Experimental evaluations are conducted to characterize the behavior of this new metric, first on a contiguity prediction task, and then via a systematic listening comparison using a conventional metric as baseline. The results underscore the viability of the proposed framework in quantifying the perception of discontinuity between acoustic units.