English-Ukrainian translation of synesthetic metaphors: Evidence from keystroke logging and corpus analysis

Abstract

Linguistic synesthesia is treated as a kind of metaphor occurring in languages commonly and naturally, like any conceptual metaphor. It is a product of mapping between two different domains of human experience, a transfer from one sensory domain (the source) to another sensory domain (the target). Combining the tools of the product- and process-oriented approaches (specifically, the keystroke logging), and the affordances of corpus linguistics, this article examines correlations between the time and cognitive effort spent on choosing a translation equivalent for the source-text synesthetic metaphoric description and its normalized frequency, indicating its degree of conventionality, and showing whether the description rests on broadly shared or linguistically culture-specific cross-sensory mappings. This research utilized the Translog-II software to record and study human translation processes. The log files containing user activity data for translating (reading, writing, and revising) were evaluated, and the results are presented and discussed. The source-text synesthetic metaphoric descriptions that fall into the isolated and marked frequency bands (NF < .1 occurrences per million words) tend to be either linguistically culture-specific or original. They pose a translation problem, the solution of which requires more cognitive effort and time, more pauses, and more frequent consultations of dictionaries and other online resources to choose the appropriate translation equivalent. The source-text synesthetic metaphoric descriptions with normalized frequency values in the majority, unmarked and dominant bands (NF ≥ .30) are generally not culture-specific and tend to have conventional translation equivalents. In such cases, the choice of translation equivalent and translation procedure is not dictated by linguistic and cultural factors, and it requires less time and cognitive effort.

CRediT Statement

Olha Zhulavska: Conceptualisation, Software, Validation, Resources, Data Curation, Writing – Original Draft, Visualisation; Alla Martyniuk: Methodology, Formal Analysis, Resources, Writing – Reviewing & Editing, Supervision, Project Administration.

Disclosure Statement

The authors reported no potential conflicts of interest.

Generative AI Statement

During the preparation of this work the authors used Grammarly, an AI-assisted writing tool, to improve the manuscript's grammar, spelling, and stylistic clarity. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the publication's content.