Feature Extraction and Model Estimation for Audio of Human Speech

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) .


Reference manual

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0.1 by Christopher Lucas, 2 months ago

Browse source code at https://github.com/cran/communication

Authors: Dean Knox [aut] , Christopher Lucas [aut, cre] , Guilherme Duarte [ctb] , Alex Shmuley [ctb] , Vineet Bansal [ctb] , Vadym Vashchenko [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, purrr, magrittr, diagram, GGally, grid, useful, ggplot2, reshape2, tuneR, wrassp, gtools, signal, plyr, RColorBrewer, scales, abind, igraph, gtable

Suggests knitr, qpdf, rmarkdown, testthat

Linking to Rcpp, RcppArmadillo

See at CRAN