Polysemy and Brevity versus Frequency in Language
Table 4: Number of analyzed and total words (by types and tokens) obtained from CHILDES conversations for each language and role. cover: percentage of words (by types or tokens) that appear in the corresponding WordNet and Wikipedia lexicon.
['[BOLD] Lang.', '[BOLD] Role', '[BOLD] Types analyzed', '[BOLD] Types total', '[BOLD] Types cover', '[BOLD] Tokens analyzed', '[BOLD] Tokens total', '[BOLD] Tokens cover']
In this paper we have studied the conversations of 60 children in English, 73 children in Dutch and 490 children in Spanish. For each spoken word of these conversations the following values are given: CHILDES frequency (number of times this word appears in CHILDES, counted separately by children and adults), Wikipedia frequency (number of times this word appears in Wikipedia), number of synsets ( according to the corresponding WordNet), number of characters, number of phonemes and number of syllables. The number of analyzed tokens and types is smaller than the number of tokens and types initially extracted from the conversations, because only those words that are present in the correspondent WordNet have been retained. Our analysis of the correlation between brevity (measured in number of characters, phonemes and syllables) and polysemy (number of synsets) versus word frequency was conducted with three correlation tests with varying assumptions and robustness. In all cases, we find correlations whose sign matches the expected sign. In addition, all correlations are significant except the Pearson correlations in the meaning-frequency law for Dutch and Spanish. This behaviour could be due to (a) the lower capacity of the Pearson correlation to detect non-linear dependencies compared to Spearman and Kendall correlations or,