Languages show systematic variation in their sound patterns and grammars. Accordingly, they have been classified into typological categories such as stress-timed vs syllable-timed, or Head-Complement (HC) vs Complement-Head (CH). To date, it has remained incompletely understood how these linguistic properties are reflected in the acoustic characteristics of speech in different languages. In the present study, the amplitude-modulation (AM) and frequency-modulation (FM) spectra of 1797 utterances in ten languages were analyzed. Overall, the spectra were found to be similar in shape across languages. However, significant effects of linguistic factors were observed on the AM spectra. These differences were magnified with a perceptually plausible representation based on the modulation index (a measure of the signal-to-noise ratio at the output of a logarithmic modulation filterbank): the maximum value distinguished between HC and CH languages, with the exception of Turkish, while the exact frequency of this maximum differed between stress-timed and syllable-timed languages. An additional study conducted on a semi-spontaneous speech corpus showed that these differences persist for a larger number of speakers but disappear for less constrained semi-spontaneous speech. These findings reveal that broad linguistic categories are reflected in the temporal modulation features of different languages, although this may depend on speaking style.
Languages show systematic variation in their sound patterns and grammars. Accordingly, they have been classified into typological categories such as stress-timed vs. syllable-timed on the basis of their rhythms, Head-Complement vs. Complement-Head on the basis of their basic word order, or tonal vs. non-tonal on the basis of the presence/absence of lexical tones. To date, it has remained incompletely understood how these linguistic properties are reflected in the acoustic characteristics of speech in different languages. In the present study, the amplitude-modulation (AM) and frequency-modulation (FM) spectra of 1862 utterances produced by 44 speakers in 12 languages were analyzed. Overall, the spectra were similar across languages. However, a perceptually based representation of the AM spectrum revealed significant differences between languages. The maximum value of this spectrum distinguished between HC non-tonal, CH non-tonal, and tonal languages, while the exact frequency of this maximum value differed between stress-timed and syllable-timed languages. Furthermore, when normalized, the f0-modulation spectra of tonal and non-tonal languages also differed. These findings reveal that broad linguistic categories are reflected in differences in temporal modulation features of different languages. This has important implications for theories of language processing and acquisition.
The ability to detect amplitude modulation (AM) is essential to distinguish the spectro-temporal features of speech from those of a competing masker. Previous work shows that AM sensitivity improves until 10 years of age. This may relate to the development of sensory factors (tuning of AM filters, susceptibility to AM masking) or to changes in processing efficiency (reduction in internal noise, optimization of decision strategies). To disentangle these hypotheses, three groups of children (5-11 years) and one of young adults completed psychophysical tasks measuring thresholds for detecting sinusoidal AM (with a rate of 4, 8, or 32 Hz) applied to carriers whose inherent modulations exerted different amounts of AM masking. Results showed that between 5 and 11 years, AM detection thresholds improved and that susceptibility to AM masking slightly increased. However, the effects of AM rate and carrier were not associated with age, suggesting that sensory factors are mature by 5 years. Subsequent modelling indicated that reducing internal noise by a factor 10 accounted for the observed developmental trends. Finally, children's consonant identification thresholds in noise related to some extent to AM sensitivity. Increased efficiency in AM detection may support better use of temporal information in speech during childhood.
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