Perceived Naturalness and Acoustic Characteristics of Habitual Versus Clear Speech for Individuals With Hearing Loss.

Abstract

Purpose: This study examined the impact of clear speech on perceived naturalness. We compared habitual speech (HS), untrained clear speech (UCS), and clear speech after a brief training (trained clear speech [TCS]) and examined whether acoustic variables differed between conditions and predicted naturalness.

Method: Twelve adult female talkers read sentences in three conditions (HS, UCS, TCS). Twenty-eight normal-hearing adults rated naturalness on a 1-9 scale. Along with naturalness, acoustic measures of speech rate, number of pauses, and pause duration were obtained and compared between speaking conditions via linear mixed-effects models (LMMs).

Results: LMMs showed a significant effect of speaking condition on the four dependent variables (p < .001), and all pairwise comparisons, except one, were significant. HS was rated most natural (3.56) and was produced at the fastest rate (3.89 syllables/s), whereas TCS was least natural (5.65) and performed at the slowest rate (1.72 syllables/s), with the most and longest pauses. All variables revealed substantial between-talkers variability in regard to baseline measures and when shifting to UCS and TCS. Speech naturalness ratings showed important between-listeners variability. Speech rate strongly predicted perceived naturalness, and the number of pauses and pause duration were also associated with it.

Conclusions: A 30-min clear speech training reduced speech naturalness compared to HS and UCS. A slower speech rate and increased pausing were associated with inferior naturalness ratings, although these features may not fully explain the reduced naturalness of TCS. The findings highlight an intelligibility-naturalness trade-off: Strategies that improve clarity can make speech sound less natural. Clinical protocols may benefit from promoting clarity-enhancing techniques that avoid excessive slowing or disruption of prosody and/or from providing real-time naturalness and intelligibility ratings as feedback during training.