Provides fast, easy feature extraction of human speech and model estimation
with hidden Markov models. Flexible extraction of phonetic features and their
derivatives, with necessary preprocessing options like feature standardization.
Communication can estimate supervised and unsupervised hidden Markov models with
these features, with cross validation and corrections for auto-correlation in
features. Methods developed in Knox and Lucas (2021) <doi:10.7910/DVN.8BTOHQ>.
| Version: |
0.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp (≥ 1.0.2), purrr, magrittr, diagram, GGally, grid, useful, ggplot2, reshape2, tuneR, wrassp, gtools, signal, plyr, RColorBrewer, scales, abind, igraph, gtable |
| LinkingTo: |
Rcpp, RcppArmadillo (≥ 0.9.700.2.0) |
| Suggests: |
knitr, qpdf, rmarkdown, testthat |
| Published: |
2021-02-25 |
| Author: |
Dean Knox [aut],
Christopher Lucas [aut, cre],
Guilherme Duarte [ctb],
Alex Shmuley [ctb],
Vineet Bansal [ctb],
Vadym Vashchenko [ctb] |
| Maintainer: |
Christopher Lucas <christopher.lucas at wustl.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
communication results |