Lobanov Normalize

Lobanov Normalize

Usage

norm_lobanov(
  .data,
  ...,
  .by = NULL,
  .by_formant = TRUE,
  .drop_orig = FALSE,
  .keep_params = FALSE,
  .names = "{.formant}_z",
  .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.

Value

A data frame of Lobanov normalized formant values.

Details

$$ \hat{F}_{ij} = \frac{F_{ij} - L_i}{S_i} $$

$$ L_i = \frac{1}{N}\sum_{j=1}^{N}F_{ij} $$

$$ S_i = \sqrt{\frac{\sum(F_{ij}-L_i)^2}{N-1}} $$

Where

• \(\hat{F}\) is the normalized formant

• \(i\) is the formant number

• \(j\) is the token number

References

Lobanov, B. (1971). Classification of Russian vowels spoken by different listeners. Journal of the Acoustical Society of America, 49, 606–608.

Examples

library(tidynorm)
ggplot2_inst <- require(ggplot2)

speaker_data_lobanov <- speaker_data |>
  norm_lobanov(
    F1:F3,
    .by = speaker,
    .names = "{.formant}_z"
  )
#> Normalization info
#> • normalized `F1`, `F2`, and `F3`
#> • normalized values in `F1_z`, `F2_z`, and `F3_z`
#> • grouped by `speaker`
#> • formant intrinsic
#> 

## this is equivalent to
# speaker_data |>
#   norm_generic(
#     F1:F3,
#     .by = speaker,
#     .by_formant = T,
#     .L = mean(.formant, na.rm = T),
#     .S = sd(.formant, na.rm = T)
#   )

if(ggplot2_inst){
  ggplot(
    speaker_data_lobanov,
    aes(
      F2_z,
      F1_z,
      color = speaker
    )
  )+
    stat_density_2d(
      bins = 4
    )+
    scale_color_brewer(
      palette = "Dark2"
    )+
    scale_x_reverse()+
    scale_y_reverse()+
    coord_fixed()
}