Analyse and Visualise Speech Rhythm and Timing Metrics

Calculates and visualises speech rhythm and timing metrics. The 'rhythm.metrics' package provides a standardised workflow to compute common metrics including Delta C, Delta V, VarcoC, VarcoV, the percentage of vocalic intervals (%V), and both raw and normalised Pairwise Variability Indices (rPVI, nPVI). It includes functions for calculating and visualising these measures to facilitate cross-linguistic and developmental rhythm research. Delta C, Delta V, and %V measures are based on Ramus et al. (1999) ; VarcoC and VarcoV measures are based on Dellwo (2006, ISBN: 9783631554777); and rPVI-C and nPVI-V are based on Grabe & Low (2002) .

rhythm.metrics

rhythm.metrics is an R package for calculating and visualising speech rhythm metrics from consonantal and vocalic interval durations.

The package provides functions for computing widely used rhythm measures, including Delta C, Delta V, Varco C, Varco V, %V, rPVI-C, and nPVI-V, as well as plotting functions for exploring and presenting results.

Note: rhythm.metrics is under active development, and additional metrics may be added in future releases.

Features

• Calculate common rhythm metrics from interval-duration data
• Summarise rhythm metrics across utterances
• Visualise rhythm metrics with ready-to-use plotting functions
• Work directly with simple data frames

Installation

You can install the development version of rhythm.metrics from GitHub:

install.packages("remotes")
remotes::install_github("congzhang365/rhythm.metrics")

Load the Package

library(rhythm.metrics)

Input Data Format

The package expects a data frame containing interval labels, utterance identifiers, and interval durations.

A typical input data frame looks like this:

df <- data.frame(
  cv_label = c(
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel"
  ),
  utterance_id = c(
    "utt_1", "utt_1", "utt_1", "utt_1",
    "utt_2", "utt_2", "utt_2", "utt_2",
    "utt_3", "utt_3", "utt_3", "utt_3",
    "utt_4", "utt_4", "utt_4", "utt_4"
  ),
  cv_duration = c(
    0.10, 0.80, 0.20, 0.50,
    0.30, 0.30, 0.40, 0.70,
    0.30, 0.88, 0.50, 0.90,
    0.30, 0.57, 0.40, 0.97
  ),
  utterance_duration = c(
    2.4, 2.4, 2.4, 2.4,
    2.7, 2.7, 2.7, 2.7,
    3.4, 3.4, 3.4, 3.4,
    1.8, 1.8, 1.8, 1.8
  )
)

Available Functions

Quick Start

Delta C and Delta V

Delta C and Delta V are rhythm metrics based on:

Ramus, F., Nespor, M., & Mehler, J. (1999). Correlates of linguistic rhythm in the speech signal. Cognition, 73(3), 265-292.

• Delta C: standard deviation of consonantal interval durations
• Delta V: standard deviation of vocalic interval durations

delta_cv(df, cv_label, utterance_id, cv_duration)

plot_delta_cv(df, cv_label, utterance_id, cv_duration)

Varco C and Varco V

Varco C and Varco V are based on:

Dellwo, V. (2006). Rhythm and Speech Rate: A Variation Coefficient for deltaC. In P. Karnowski & I. Szigeti (Eds.), Language and language-processing (pp. 231-241). Peter Lang.

• Varco C: Delta C / mean consonant duration * 100
• Varco V: Delta V / mean vowel duration * 100

varco_cv(df, cv_label, utterance_id, cv_duration)

plot_varco_cv(df, cv_label, utterance_id, cv_duration)

Percentage of Vocalic Intervals (%V)

%V is based on:

Ramus, F., Nespor, M., & Mehler, J. (1999). Correlates of linguistic rhythm in the speech signal. Cognition, 73(3), 265-292.

It measures the percentage of total utterance duration occupied by vocalic material.

percentage_v(df, v_label = "vowel", utterance_id, cv_duration, utterance_duration)

plot_percentage_v(df, cv_label, label_name = "vowel", 
                  utterance_id, cv_duration, utterance_duration)

rPVI-C

rPVI-C is based on:

Grabe, E., & Low, E. L. (2002). Durational variability in speech and the rhythm class hypothesis. In Laboratory Phonology 7 (pp. 515-546). De Gruyter Mouton.

It calculates the average absolute difference between consecutive consonantal intervals.

rpvi_c(df, cv_label, label_name = "consonant", utterance_id, cv_duration)

plot_rpvi(df, cv_label, label_name = "consonant", utterance_id, cv_duration)

nPVI-V

nPVI-V is based on:

Grabe, E., & Low, E. L. (2002). Durational variability in speech and the rhythm class hypothesis. In Laboratory Phonology 7 (pp. 515-546). De Gruyter Mouton.

It calculates the normalised average absolute difference between consecutive vocalic intervals.

npvi_v(df, cv_label, label_name = "vowel", utterance_id, cv_duration)

plot_npvi(df, cv_label, label_name = "vowel", utterance_id, cv_duration)

Example Workflow

A simple workflow with the package might look like this:

library(rhythm.metrics)

df <- data.frame(
  cv_label = c(
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel",
    "consonant", "vowel", "consonant", "vowel"
  ),
  utterance_id = c(
    "utt_1", "utt_1", "utt_1", "utt_1",
    "utt_2", "utt_2", "utt_2", "utt_2",
    "utt_3", "utt_3", "utt_3", "utt_3",
    "utt_4", "utt_4", "utt_4", "utt_4"
  ),
  cv_duration = c(
    0.10, 0.80, 0.20, 0.50,
    0.30, 0.30, 0.40, 0.70,
    0.30, 0.88, 0.50, 0.90,
    0.30, 0.57, 0.40, 0.97
  ),
  utterance_duration = c(
    2.4, 2.4, 2.4, 2.4,
    2.7, 2.7, 2.7, 2.7,
    3.4, 3.4, 3.4, 3.4,
    1.8, 1.8, 1.8, 1.8
  )
)

# Analysis
delta_cv(df, cv_label, utterance_id, cv_duration)
varco_cv(df, cv_label, utterance_id, cv_duration)
percentage_v(df, v_label = "vowel", utterance_id, cv_duration, utterance_duration)
rpvi_c(df, cv_label, label_name = "consonant", utterance_id, cv_duration)
npvi_v(df, cv_label, label_name = "vowel", utterance_id, cv_duration)

# Visualisation
plot_delta_cv(df, cv_label, utterance_id, cv_duration)
plot_varco_cv(df, cv_label, utterance_id, cv_duration)
plot_percentage_v(df, cv_label, label_name = "vowel", 
                  utterance_id, cv_duration, utterance_duration)
plot_rpvi(df, cv_label, label_name = "consonant", utterance_id, cv_duration)
plot_npvi(df, cv_label, label_name = "vowel", utterance_id, cv_duration)

Documentation

For more detailed examples and usage notes, see the package vignette and function help pages after installation.

?delta_cv
?varco_cv
?percentage_v
?rpvi_c
?npvi_v

Citation

If you use rhythm.metrics in your research, please cite:

Zhang, C. (2022). A Guide for the R Package "rhythm_metrics". OSF Preprints. https://doi.org/10.31219/osf.io/kfnzt

You can also obtain the package citation from R with:

citation("rhythm.metrics")

BibTeX for the 2022 guide:

@misc{zhang2022,
  title  = {A Guide for the R Package "rhythm_metrics"},
  author = {Zhang, Cong},
  year   = {2022},
  doi    = {10.31219/osf.io/kfnzt},
  url    = {https://doi.org/10.31219/osf.io/kfnzt}
}

Contributing

Bug reports, feature requests, and suggestions are welcome. If you encounter an issue or would like to suggest an additional metric, please open an issue on GitHub or email me at [email protected]

License

GPL-3