Delta F Normalize
Usage
norm_deltaF(
.data,
...,
.by = NULL,
.by_formant = FALSE,
.drop_orig = FALSE,
.keep_params = FALSE,
.names = "{.formant}_df",
.silent = FALSE
)
Arguments
- .data
A data frame containing vowel formant data
- ...
<tidy-select>
One or more unquoted expressions separated by commas. These should target the vowel formant data columns.- .by
<tidy-select>
A selection of columns to group by. Typically a column of speaker IDs.- .by_formant
Ignored by this procedure
- .drop_orig
Whether or not to drop the original formant data columns.
- .keep_params
Whether or not to keep the Location (
*_.L
) and Scale (*_.S
) normalization parameters- .names
A
glue::glue()
expression for naming the normalized data columns. The"{.formant}"
portion corresponds to the name of the original formant columns.- .silent
Whether or not the informational message should be printed.
Details
$$ \hat{F}_{ij} = \frac{F_{ij}}{S} $$ $$ S = \frac{1}{MN}\sum_{i=1}^M\sum_{j=1}^N \frac{F_{ij}}{i-0.5} $$
Where
\(\hat{F}\) is the normalized formant
\(i\) is the formant number
\(j\) is the token number
References
Johnson, K. (2020). The ΔF method of vocal tract length normalization for vowels. Laboratory Phonology: Journal of the Association for Laboratory Phonology, 11(1), Article 1. https://doi.org/10.5334/labphon.196
Examples
library(tidynorm)
ggplot2_inst <- require(ggplot2)
speaker_data_deltaF <- speaker_data |>
norm_deltaF(
F1:F3,
.by = speaker,
.names = "{.formant}_df"
)
#> Normalization info
#> • normalized `F1`, `F2`, and `F3`
#> • normalized values in `F1_df`, `F2_df`, and `F3_df`
#> • grouped by `speaker`
#> • formant extrinsic
#>
## this is equivalent to
# speaker_data |>
# norm_generic(
# F1:F3,
# .by = speaker,
# .S = mean(.formant/(.formant_num - 0.5), na.rm = T)
# )
if(ggplot2_inst){
ggplot(
speaker_data_deltaF,
aes(
F2_df,
F1_df,
color = speaker
)
)+
stat_density_2d(
bins = 4
)+
scale_color_brewer(
palette = "Dark2"
)+
scale_x_reverse()+
scale_y_reverse()+
coord_fixed()
}