nzilbb.vowels (version 0.3.1)

lobanov_2: Apply Lobanov 2.0 normalisation

Description

lobanov_2() takes a data frame where the first four columns are:

1. speaker identifiers,

2. vowel identifiers,

3. first formant values in Hertz,

4. second formant values in Hertz.

It returns a dataframe with two additional columns, F1_lob2 and F2_lob2, containing normalised formant values.

Usage

lobanov_2(vowel_data)

Value

a dataframe matching the input dataframe with additional columns F1_lob2 and F2_lob2, containing the lobanov normalised F1 and F2 values respectively.

Arguments

vowel_data

a dataframe whose first four columns are speaker ids, vowel ids, F1 values, and F2 values.

Details

This functions applies Lobanov 2.0 normalisation presented in Brand et al. (2021). This variant of Lobanov normalisation is designed to work for datasets whether the vowel types have different token counts from one another. The Lobanov 2.0 value for a vowel is given by $$F_{lobanov2.0_i} = \frac{F_{raw_i} - \mu(\mu_{vowel_1}, \ldots, \mu_{vowel_n})}{\sigma(\mu_{vowel_1}, \ldots, \mu_{vowel_n})}$$ where, for ease of notation, we assume all values are from a single speaker. We signify the n vowel types as vowel_1, ..., vowel_2, while i indicates the formant number. We implement the function for F1 and F2.

References

Brand, James, Jen Hay, Lynn Clark, Kevin Watson & Márton Sóskuthy (2021): Systematic co-variation of monophthongs across speakers of New Zealand English. Journal of Phonetics. Elsevier. 88. 101096. doi:10.1016/j.wocn.2021.101096

Examples

normed_vowels <- lobanov_2(onze_vowels)
head(normed_vowels)