H omophone2 V ec: Embedding Space Analysis for Empirical Evaluation of Phonological and Semantic Similarity (2024)

Abstract: This paper introduces a novel method for empirically evaluating the relationship between the phonological and semantic similarity of linguistic units using embedding spaces. Chinese character homophones are used as a proof-of-concept. We employ cosine similarity as a proxy for semantic similarity between characters, and compare relationships between phonologically-related characters and baseline characters (chosen as similar-frequency characters). We show there is a strongly statistically significant positive semantic relationship among different Chinese characters at varying levels of sound-sharing. We also perform some basic probing using t-SNE and UMAP visualizations, and indicate directions for future applications of this method.

## introduction homophones -linguistic units with the same sound but different meanings -evidently produce semantic ambiguity within language. however, certain functional linguistic theories suggest that ambiguity may actually allow for greater linguistic efficiency, by enabling language learners to better use finite phonological space (i.e. limitations on the word length and sounds in a language) @xcite . it remains uncertain to what degree linguistically ambiguous input such as homophones require highly differentiable semantic/syntactic contexts for processing, or whether this is generalizable across languages. studies in french and english have indicated that homophony may have either an insignificant or inhibitory effect on language processing @xcite . fieldwork in these languages have also shown that homophones with different syntactic contexts and semantic meanings are easier for children to memorize @xcite . these studies widely assert that homophones should have different se-mantic and syntactic functions to survive in a language. however, in chinese, a language where many characters have high frequency homophone mates, studies have actually indicated that semantically similar homophones can be facilitate lexical decision-making @xcite , and acquisition of new words @xcite . do homophones necessitate high semantic dissimilarity? this paper proposes a novel method of using word embedding spaces to empirically investigate this question by using embedding space properties to determine statistically significant relationships between phonological and semantic similarity. our method involves comparing the cosine similarity between embeddings of homophone pairs to baseline similarities, where we find baselines using similar-frequency characters. we choose a pre-trained embedding space optimized to encode both semantic and syntactic information, and then use this space to look for a statistically significant difference in homophone and baseline similarity. this methodology can be extended to other languages and linguistic units, but we first turn to chinese character homophones, which offer an interesting avenue of investigation into homophony due to the previous literature arguing for their unique role in language. the densely packed phonological space of chinese characters, along with the ease of accessing standard sounds from chinese characters, also provide a straightforward proof-of-concept for our method. ## results based on our similarity comparisons, we find that there is a highly statistically significant effect of homophony and pseudo-homophony on increasing cosine similarity, and a slightly less significant effect of characters with the same initial sound (in the opposite direction), but no significant effect on characters which share the same vowels. results are shown in in table ??, n displays the sample size for each group. this varies because different numbers of comparisons can be made for each relationship, but since we generate baselines proportionately to each target group, this should not impact the results. the coefficient can be interpreted as the amount which a one-unit addition in similarity impacts the likelihood of the comparison belonging to the target relationship (e.g. homophone) rather than the baseline comparison. the positive coefficient for homophones and pseudo-homophones, alongside the high level of significance (p-@xmath0.05 in all cases except same-vowel comparisons), indicate that increased proximity in the embedding space (which we use as a proxy for increased semantic similarity) increase the probability of a comparison sharing similar phonological features according to our model. other results are analyzed further in the discussion section. ## discussion based on our results, we find evidence that phonological similarity and semantic similarity are correlated in chinese. however, since words with the same initial sound exhibit semantic dissimilarity (albeit with a coefficient of smaller magnitude than for coefficient for homophones or pseudohomophones, and with slightly less statistical significance), there may be a particular semantic role that is played by characters that share all sounds that cannot just be explained by the general level of phonological similarity. this is especially supported by the lack of statistically significant relationship for characters that share the same vowel sound. if we interpret the embedding similarity purely as a measure of the syntactic environments which these characters are likely to occur in, the fact that homophones are more likely to share syntactic environments challenges the theory that language users rely explicitly on different syntactic context to avoid linguistic ambiguity. further, if we use the distributional hypothesis to assume that this embedding similarity is representative of the semantic similarity between homophones, our findings dispute the idea that homophones must be semantically distant to survive or be effectively used in a language. this also corroborates the work of linguistic studies that have shown that encoding similar semantic information into words with phonological similarity may be more efficient for learning chinese. our t-sne and umap plots confirm these results, and also indicate that homophones exhibit different levels of similarity at the local and global level of the embedding space. future probing could potentially determine what this discrepancy implies for the semantic relationship between homophones.