tidynorm (version 0.4.0)

norm_generic: Generic Normalization Procedure

Description

This is a generic normalization procedure with which you can create your own normalization method.

Usage

norm_generic(
  .data,
  ...,
  .by = NULL,
  .by_formant = FALSE,
  .by_token = FALSE,
  .L = 0,
  .S = 1,
  .pre_trans = function(x) x,
  .post_trans = function(x) x,
  .drop_orig = FALSE,
  .keep_params = FALSE,
  .names = "{.formant}_n",
  .silent = opt("tidynorm.silent"),
  .call = caller_env()
)

Value

A data frame of normalized formant values

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

Whether or not the normalization method is formant intrinsic.

.by_token

Whether or not the normalization method is vowel intrinsic

.L

An expression defining the location parameter. See Details for more information.

.S

An expression defining the scale parameter. See Details for more information.

.pre_trans

A function to apply to formant values before normalization.

.post_trans

A function to apply to formant values after normalization.

.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

Suppress normalization information messages when running a norm_*() function. (Defaults to FALSE, overwritable using option 'tidynorm.silent' or environment variable 'R_TIDYNORM_TIDYNORM_SILENT')

.call

Used for internal purposes.

Details

The following norm_* procedures are built on top of norm_generic().

• norm_lobanov

• norm_nearey

• norm_deltaF

• norm_wattfab

• norm_barkz

Location and Scale expressions

All normalization procedures built on norm_generic produce normalized formant values (\(\hat{F}\)) by subtracting a location parameter (\(L\)) and dividing by a scale parameter (\(S\)).

$$ \hat{F} = \frac{F-L}{S} $$

The expressions for calculating \(L\) and \(S\) can be passed to .L and .S, respectively. Available values for these expressions are

.formant

The original formant value

.formant_num

The number of the formant. (e.g. 1 for F1, 2 for F2 etc)

Along with any data columns from your original data.

Pre and Post normalization transforms

To apply any transformations before or after normalization, you can pass a function to .pre_trans and .post_trans.

Formant In/Extrinsic Normalization

If .by_formant is TRUE, normalization will be formant intrinsic. If .by_formant is FALSE, normalization will be formant extrinsic.

Token In/Extrinsic Normalization

If .by_token is TRUE, normalization will be token intrinsic. If .by_token is FALSE, normalization will be token extrinsic.

Examples

library(tidynorm)
library(dplyr)

speaker_data |>
  norm_generic(
    F1:F3,
    .by = speaker,
    .by_formant = TRUE,
    .L = median(.formant, na.rm = TRUE),
    .S = mad(.formant, na.rm = TRUE),
    .drop_orig = TRUE,
    .names = "{.formant}_mad"
  )