ArticularlyWordRecognition {mlmts}

ArticularyWordRecognition

Description

Multivariate time series (MTS) of movements of tongue and lips during speech. The data were collected from multiple native English speakers producing 25 words.

Usage

data(ArticularlyWordRecognition)

Format

A list with two elements, which are:

data

A list with 575 MTS.

classes

A numeric vector indicating the corresponding classes associated with the elements in data.

Details

Each element in data is a matrix formed by 144 rows (time points) indicating movement and 9 columns (variables) indicating sensors. The first 275 elements correspond to the training set, whereas the last 300 elements correspond to the test set. The numeric vector classes is formed by integers from 1 to 25, indicating that there are 25 different classes in the database. Each class is associated with a different word produced by the speaker. For more information, see Bagnall et al. (2018). Run "install.packages("ueadata1", repos="https://anloor7.github.io/drat")" to access this dataset and use the syntax "ueadata1::ArticularyWordRecognition".

References

Bagnall A, Dau HA, Lines J, Flynn M, Large J, Bostrom A, Southam P, Keogh E (2018). “The UEA multivariate time series classification archive, 2018.” arXiv preprint arXiv:1811.00075.

Ruiz AP, Flynn M, Large J, Middlehurst M, Bagnall A (2021). “The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances.” Data Mining and Knowledge Discovery, 35(2), 401–449.

Bagnall A, Lines J, Vickers W, Keogh E (2022). “The UEA & UCR Time Series Classification Repository.” www.timeseriesclassification.com.