speaker_jsd: Group-level JSD point estimates

In phontrast: Contrast and Separation Metrics for Phonological Categories

Group-level JSD point estimates

Description

Computes JSD for each group (e.g., speaker) comparing two categories (e.g., vowels) in an n-dimensional acoustic space.

Usage

speaker_jsd(
  data,
  group_col,
  category_col,
  features,
  min_tokens = 20,
  bw = c("Hpi", "Hscv", "Hpi.diag", "scott.diag"),
  eval_on = c("pooled", "group1", "group2", "pooled_sample"),
  eval_n = NULL,
  eval_seed = NULL,
  engine = c("ks", "fast_diag", "fast_diagonal"),
  chunk_size = 1000L,
  ...
)

Arguments

data	Data frame containing acoustic measurements.
group_col	Character vector giving one or more grouping columns (e.g., "speaker" or c("Sex", "Style")).
category_col	String: name of column giving the category to compare (e.g., "vowel"). Each group must have exactly two categories.
features	Character vector of column names giving the acoustic space.
min_tokens	Minimum number of tokens per group required to compute JSD. Groups with fewer tokens are dropped.
bw	Bandwidth selection method passed to jsd_kde_nd().
eval_on	KDE evaluation points passed to jsd_kde_nd().
eval_n	Optional maximum number of KDE evaluation points.
eval_seed	Optional integer seed for KDE evaluation-point subsampling.
engine	KDE evaluation engine passed to jsd_kde_nd(). "fast_diagonal" is accepted as an alias for "fast_diag".
chunk_size	Chunk size for engine = "fast_diag".
...	Additional arguments passed to jsd_kde_nd().

Value

A tibble with one row per group and columns: group, n_tokens, and jsd.

phontrast documentation built on Oct. 7, 2026, 5:06 p.m.