Cross-linguistic Influences on Sentence Accent Detection in Background Noise

Abstract

This paper investigates whether sentence accent detection in a non-native language is dependent on (relative) similarity between prosodic cues to accent between the non-native and the native language, and whether cross-linguistic differences in the use of local and more widely distributed (i.e., non-local) cues to sentence accent detection lead to differential effects of the presence of background noise on sentence accent detection in a non-native language. We compared Dutch, Finnish, and French non-native listeners of English, whose cueing and use of prosodic prominence is gradually further removed from English, and compared their results on a phoneme monitoring task in different levels of noise and a quiet condition to those of native listeners. Overall phoneme detection performance was high for the native and the non-native listeners, but deteriorated to the same extent in the presence of background noise. Crucially, relative similarity between the prosodic cues to sentence accent of one’s native language compared to that of a non-native language does not determine the ability to perceive and use sentence accent for speech perception in that non-native language. Moreover, proficiency in the non-native language is not a straightforward predictor of sentence accent perception performance, although high proficiency in a non-native language can seemingly overcome certain differences at the prosodic level between the native and non-native language. Instead, performance is determined by the extent to which listeners rely on local cues (English and Dutch) versus cues that are more distributed (Finnish and French), as more distributed cues survive the presence of background noise better.

Acoustic Identification of Sentence Accent in Speakers with Dysarthria: Cross-Population Validation and Severity Related Patterns

“…This set of features was used in a discriminant function to classify between accented and unaccented syllables, achieving 91.9% of correct classification of accented syllables and 92.2% of correct classification of unaccented syllables for the new population of English speakers affected with ataxic dysarthria. The classification accuracy results are comparable with the results of our previous study for native Dutch speakers (healthy and dysarthric speech) and with other studies of accent detection in healthy speech [30][31][32][33][34][35]. The results suggest that combining the ten acoustic parameters developed by Mendoza et al [41] has a good capacity to discriminate between accented and unaccented syllables in healthy and speech-impaired speakers of Germanic languages with comparable accentuation patterns, such as English and Dutch.…”

“…Studies of acoustic correlates of sentence accent have provided valuable insight into this domain [12,[25][26][27][28][29]. Acoustic accent production descriptors have been studied in healthy speech [30][31][32][33][34][35][36][37] and in dysarthria [9,10,16,24,38,39]. Currently, there is general agreement in the literature that syllable duration, pitch pattern, and intensity (or sub-band energy) correlate with accentuation [26,40].…”