کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
566251 | 875957 | 2009 | 17 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Measuring Norwegian dialect distances using acoustic features Measuring Norwegian dialect distances using acoustic features](/preview/png/566251.png)
Levenshtein distance has become a popular tool for measuring linguistic dialect distances, and has been applied to Irish Gaelic, Dutch, German and other dialect groups. The method, in the current state of the art, depends upon phonetic transcriptions, even when acoustic differences are used the number of segments in the transcriptions is used for speech rate normalization.The goal of this paper is to find a fully acoustic measure which approximates the quality of semi-acoustic measures that rely on tagged speech. We use a set of 15 Norwegian dialect recordings and test the hypothesis that the use of the acoustic signal only, without transcriptions, is sufficient for obtaining results which largely agree with both traditional Norwegian dialectology and the perception of the speakers themselves.We use formant trajectories and consider both the Hertz and the Bark scale. We experiment with an approach in which z-scores per frame are used instead of the original frequency values. Besides formant tracks, we also consider zero crossing rates: the number of times per interval that the amplitude waveform crosses the zero line. The zero crossing rate is sensitive to the difference between voiced and unvoiced speech sections.When using the fully acoustic measure on the basis of the combined representation with normalized frequency values, we obtained results comparable with the results obtained with the semi-acoustic measure. We applied cluster analysis and multidimensional scaling to distances obtained with this method and found results which largely agree with both the results of traditional Norwegian dialectology and with the perception of the speakers. When scaling to three dimensions, we found the first dimension responsible for gender differences. However, when leaving out this dimension, dialect specific information is lost as well.
Journal: Speech Communication - Volume 51, Issue 2, February 2009, Pages 167–183