VOWELS IN STANDARD AUSTRIAN GERMAN - Acoustics ...

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Sylvia Moosmüller Although Figure 7.2 suggests significant differences between the three speakers by means of F3, these differences cannot withstand a statistical analysis. Neither a two- tailed t-test nor the z-deviation renders differences for F3 between sp126 and sp127. One could argue that a visual comparison of the distributions might suffice to keep the speakers apart. However, in a cross-check comparison of one and the same speaker in different speaking tasks, the distribution of formants need not result in a satisfying overlap either. Figure 7.3 shows a density plot of all vowels /ç/ from “nicht” (not) of one speaker (sp126) in the sentence reading task and in spontaneous speech: c(xmin, xmax) 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 1500 2000 2500 3000 3500 Figure 7.3: Density plot of F2 and F3 of the vowel /ç/ from “nicht” (not), sentence reading task (red) and spontaneous speech (black), n = 18. Index A visual inspection would render differences for F3. Calculated z-scores, however, correctly prove accordance for the /ç/ of spontaneous speech with the /ç/ of the sentence reading task with respect to both F2 and F3. 240
241 Vowels in Standard Austrian German It might be argued that a sufficient number (~ 3-4) of several identical items (~ 20) in both the questioned and the reference material would lead to a successful comparison. Apart from the fact that in a true forensic case, a sufficient number of several identical items are hardly ever available, this hypothesis does not bear up either. Table 7.10 shows the results of the statistical analysis of a comparison of several items which were available in the spontaneous speech of all three male speakers. Item Sp012 – Sp126 Sp012 – Sp127 Sp126 – Sp127 geboren (born: PP) – – – aufgewachsen (grew up (PP) + + + bin (be: 1P) + + – mit (with) – – – dann (then) – – – hat (has: 3P) + NA NA hab (have: 1P) NA NA – Table 7.10: Results of the statistical analysis (F2 and F3) for vowels in identical phonetic context, spontaneous speech. “+”: p < 0.05 for either F2 or F3 or both, “–“: p > 0.05, NA = not enough data available. As can be seen from Table 7.10, even the discriminatory power of identical items is rather poor. Therefore, it is not only necessary to control the phonetic context, which actually means the word, but to additionally control the position within the sentence or utterance. It has already been argued in 6.5 that the clearer the context is defined, the sooner invariant patterns will be observed. This finding, as well as the results on prosody, imply some space for speaker-specific handling of variability. Therefore, an acoustic analysis of the same word in the same position will the soonest and the most frequently be able to differentiate speakers and to recognize identical speakers. Figure 7.4 presents the cluster analysis of the vowel /i/ from “die” (the:DEF):
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VOWELS IN STANDARD AUSTRIAN GERMAN
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Vowels in Standard Austrian German
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1. Introduction: Setting the Theore
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3 Vowels in Standard Austrian Germa
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11 Vowels in Standard Austrian Germ
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Hz 3000 2500 2000 1500 1000 500 0 N
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� Speaker sp127: Student, male, 2
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4. Vowel inventory and features 51
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Spontaneous speech Long vowel + len
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Spontaneous speech Long vowel + len
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Height 0 10 20 30 40 u i o ö ü e
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Vowel category Variability Coeffici
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5.3. Processes vs. Coarticulation 1
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� F3 shows a high variability in
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c(xmin, xmax) 0.000 0.001 0.002 0.0
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6.2. Undershoot vs. Processes 179 V
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Hz 3500 3000 2500 2000 1500 1000 50
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Page 215 and 216: Variability coefficient 40,000 35,0
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