Phoneme Intelligibility of Four Text-to-Speech Products to Nonnative Speakers of English in Noise

Abstract

The study investigated the segmental intelligibility of four text-to-speech (TTS) products under 0 dB and 5 dB signal-to-noise ratios in a group of native and nonnative speakers of English. Each product—AT&T Next-Gen™, Festival version 1.4.2, FlexVoice™ 2, and IBM ViaVoice™ Version 5.1—uses a different algorithm for generating speech from text. The results, which benefit developers of TTS technology as well as developers of products that utilize TTS, showed that (1) all TTS products were less intelligible to nonnative speakers of English than native speakers, (2) the “hybrid” TTS product that combined concatenative and formant synthesis methods was the least intelligible of the four products investigated, (3) the remaining three products, which used formant, concatenative diphone based LPC, and concatenative waveform synthesis methods respectively, were equally intelligible to nonnative speakers, (4) none of the four TTS products was better at resisting intelligibility loss due to noise than others, and (5) listening to currently available unrestricted TTS under high noise conditions would probably require a greater amount of cognitive resources on the part of both native and nonnative speakers of English and may be difficult when other demanding activities are concurrently performed.