This paper presents a systematic comparison of various measures of f0 range in female speakers of English and German. F0 range was analyzed along two dimensions, level (i.e., overall f0 height) and span (extent of f0 modulation within a given speech sample). These were examined using two types of measures, one based on “long-term distributional” (LTD) methods, and the other based on specific landmarks in speech that are linguistic in nature (“linguistic” measures). The various methods were used to identify whether and on what basis or bases speakers of these two languages differ in f0 range. Findings yielded significant cross-language differences in both dimensions of f0 range, but effect sizes were found to be larger for span than for level, and for linguistic than for LTD measures. The linguistic measures also uncovered some differences between the two languages in how f0 range varies through an intonation contour. This helps shed light on the relation between intonational structure and f0 range.
Background Occupational voice problems constitute a serious public health issue with substantial financial and human consequences for society. Modern mobile technologies such as smartphones have the potential to enhance approaches to prevention and management of voice problems. This paper addresses an important aspect of smartphone‐assisted voice care: the reliability of smartphone‐based acoustic analysis for voice health state monitoring. Aim To assess the reliability of acoustic parameter extraction for a range of commonly used smartphones by comparison with studio recording equipment. Methods & Procedures Twenty‐two vocally healthy speakers (12 female, 10 male) were recorded producing sustained vowels and connected speech under studio conditions using a high‐quality studio microphone and an array of smartphones. For both types of utterance, Bland–Altman analysis was used to assess overall reliability for mean F0, cepstral peak prominence (CPPS), Jitter (RAP) and Shimmer %. Outcomes & Results Analysis of the systematic and random error indicated significant bias for CPPS across both sustained vowels and passage reading. Analysis of the random error of the devices indicated that that mean F0 and CPPS showed acceptable random error size, while jitter and shimmer random error was judged as problematic. Conclusions & Implications Confidence in the feasibility of smartphone‐based voice assessment is increased by the experimental finding of high levels of reliability for some clinically relevant acoustic parameters, while the use of other parameters is discouraged. We also challenge the practice of using statistical tests (e.g., t‐tests) for measurement reliability assessment.
While it is well known that languages have different phonemes and phonologies, there is growing interest in the idea that languages may also differ in their 'phonetic setting'. The term 'phonetic setting' refers to a tendency to make the vocal apparatus employ a languagespecific habitual configuration. For example, languages may differ in their degree of lip-rounding, tension of the lips and tongue, jaw position, phonation types, pitch range and register. Such phonetic specifications may be particularly difficult for second language (L2) learners to acquire, yet be easily perceivable by first language (L1) listeners as inappropriate. Techniques that are able to capture whether and how an L2 learner's pronunciation proficiency in their two languages relates to the respective phonetic settings in each language should prove useful for second language research. This article gives an overview of a selection of techniques that can be used to investigate phonetic settings at the articulatory level, such as fleshpoint tracking, ultrasound tongue imaging and electropalatography (EPG), as well as a selection of acoustic measures such as measures of pitch range, long-term average spectra and formants.Keywords: language-specific phonetic settings, cross-language production of phonetic settings in L2 learners, segmental aspects of speech learning, prosodic aspects of speech learning, articulatory measures, inter-speech postures, articulatory techniques, electromagnetic articulography (EMA), ultrasound tongue imaging 14 Language-specifi c phonetic settings (UTI), electropalatography (EPG), flesh-point tracking, L2 phonetics, pitch range, formant analysis, long-term average spectra (LTAS)
This study examined whether rapid temporal auditory processing, verbal working memory capacity, non-verbal intelligence, executive functioning, musical ability and prior foreign language experience predicted how well native English speakers (N = 120) discriminated Norwegian tonal and vowel contrasts as well as a non-speech analogue of the tonal contrast and a native vowel contrast presented over noise. Results confirmed a male advantage for temporal and tonal processing, and also revealed that temporal processing was associated with both non-verbal intelligence and speech processing. In contrast, effects of musical ability on non-native speech-sound processing and of inhibitory control on vowel discrimination were not mediated by temporal processing. These results suggest that individual differences in non-native speech-sound processing are to some extent determined by temporal auditory processing ability, in which males perform better, but are also determined by a host of other abilities that are deployed flexibly depending on the characteristics of the target sounds.
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