Abstract
A variation of log-mean normalization that can be applied in cross-language and cross-dialect experiments, is presented. Vowel normalization procedures seek to remove inter-speaker variance due to factors such as vocal tract size, which human listeners discount while identifying vowels. It is expected that the mean vocal-tract length are approximately equal over large and sufficiently balanced samples of speakers. The cross-language normalization procedure is tested using acoustic data from productions of L1-Spanish non-low front vowels and L1 English non-low front vowels. Three models are trained and tested using non-normalized log-Hertz values, language-normalized values, and cross-language normalized values respectively. The models trained on normalized L1-English vowels had a slightly higher correct-classification rate on the training data than the model trained on non-normalized data. The vowel normalization increased the correlation between monolingual English listeners.
| Original language | English |
|---|---|
| Pages (from-to) | 94-95 |
| Number of pages | 2 |
| Journal | Canadian Acoustics - Acoustique Canadienne |
| Volume | 34 |
| Issue number | 3 |
| Publication status | Published - Sept 2006 |
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