  This research project aimed to overcome the challenge of analysing human
language relationships, facilitate the grouping of languages and formation of
genealogical relationship between them by developing automated comparison
techniques. Techniques were based on the phonetic representation of certain key
words and concept. Example word sets included numbers 1-10 (curated), large
database of numbers 1-10 and sheep counting numbers 1-10 (other sources),
colours (curated), basic words (curated).
  To enable comparison within the sets the measure of Edit distance was
calculated based on Levenshtein distance metric. This metric between two
strings is the minimum number of single-character edits, operations including:
insertions, deletions or substitutions. To explore which words exhibit more or
less variation, which words are more preserved and examine how languages could
be grouped based on linguistic distances within sets, several data analytics
techniques were involved. Those included density evaluation, hierarchical
clustering, silhouette, mean, standard deviation and Bhattacharya coefficient
calculations. These techniques lead to the development of a workflow which was
later implemented by combining Unix shell scripts, a developed R package and
SWI Prolog. This proved to be computationally efficient and permitted the fast
exploration of large language sets and their analysis.
