Effects of auditory, visual and gestural input on the perceptual learning of tones

In this study, we outline a methodology to quantify the degree of similarity between pairs of f0 distributions based on the Anderson-Darling measure that underlies its namesake goodness-of-fit test. The procedure emphasizes differences due to more fine-grained f0 modulations rather than differences in measures of central tendency, such as the mean and median. In order to assess the procedure's usefulness for speaker comparison, we applied it to a multilingual corpus in which participants contributed speech delivered in three speaking styles. The similarity measure was calculated separately as function of speaking style and speaker. Between-speaker variability (different speakers, same style) in distribution similarity varied significantly between styles-spontaneous interview shows greater variability than read sentences and word list in five languages (English, French, Italian, Portuguese and Swedish); in Estonian and German, read sentences yield more variability. Within-speaker variability (same speaker, different styles) levels are lower than between-speaker in the style that exhibit the greatest variability. The results point to the potential use of the proposed methodology as a way to identify possible idiosyncratic traits in f0 distributions. Also, they further demonstrate the effect of speaking styles on intonation patterns.

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“…Prior to test application, raw values in the f0 contours were converted to the OMe scale, proposed by [13], using the formula…”

Section: Measuring F0 Distribution Similaritymentioning

confidence: 99%

Quantifying Fundamental Frequency Modulation as a Function of Language, Speaking Style and Speaker

Arantes

Eriksson

2019

Interspeech 2019

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“…These measurements were conducted on the continuous pitch contours modeled by Momel algorithm using a Praat plugin [9]. They were normalized to eliminate individual differences using the OMe (Octave-Median) scale [10]. In addition, (8) speech rate and (9) mean intensity were also included.…”

Section: Acoustic Measurementsmentioning

confidence: 99%

Are pitch variation cues indispensable to distinguish vocal emotions?

Wang¹,

Yang²

2018

Speech Prosody 2018

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Pitch variation (e.g., pitch movement and range) has been proved to be one of the most important cues in encoding and distinguishing emotions in speech. However, it has been found that pitch variation could be restricted due to the existence of lexical tones in Mandarin, resulting in the failure of distinguishing emotions through pitch variation cues. Based on this finding, we conducted both production and perception experiments to explore whether pitch variation cues were indispensable for listeners to identify emotions. Results of the production experiment demonstrated that there was no significant effect of Emotion on pitch variation cues in T1 group (all high level tone sequences) in Mandarin, suggesting that in some case, pitch variation may not be effective for encoding emotions. However, results of the perception experiment confirmed that the identification rates of emotions among five tone groups had no significant differences. Therefore, we posit that listeners may not always use pitch variation cues to identify emotions in speech. There might be a gap between the analyzed prosodic cues in the production experiment and the cues used by listeners.

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“…These parameters were captured by both global and local pitch movements of each sentence. Pitch-related parameters were normalized to eliminate individual differences using the OMe (Octave-Median) scale [15] by applying the following equation:…”

Section: Measurementsmentioning

confidence: 99%

An experimental study of emotional speech in Mandarin and English

Wang¹,

Lee²,

Ma³

2016

Speech Prosody 2016

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This study reports our initial results on whether the use of pitch for expressing emotions differs between Mandarin and English. The production experiment was conducted using five emotions (anger, fear, happiness, sadness, and neutral) by comparing both prosodic cues and phonation cues between Mandarin and English emotional speech. Results demonstrated that within each language, each vocal emotion had specific acoustic patterns. Moreover, Mandarin and English showed different mechanisms of utilizing pitch for encoding emotions. The differences in pitch variation between neutral and other emotions were significantly larger in English than in Mandarin. However, the variations of speech rate and certain phonation cues (e.g., CPP and CQ) were significantly larger in Mandarin than in English. The differences in emotional speech between the two languages may be due to the restriction of pitch variation by the presence of lexical tones in Mandarin. This study reveals an interesting finding that when a certain parameter (e.g., pitch) is restricted in one language, other cues turned out to be strengthened for compensation. Therefore, we posit that the acoustic realizations of emotional speech are multidimensional.

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Effects of auditory, visual and gestural input on the perceptual learning of tones

Cited by 13 publications

References 11 publications

Quantifying Fundamental Frequency Modulation as a Function of Language, Speaking Style and Speaker

Quantifying Fundamental Frequency Modulation as a Function of Language, Speaking Style and Speaker

Are pitch variation cues indispensable to distinguish vocal emotions?

An experimental study of emotional speech in Mandarin and English

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