Speech Recognition Technology in Cognitive Translation Studies

TLDR: The results of this study have some implications for the translation process: the syntax analysis shows that in most cases the translators managed to produce natural word order in target sentences; switching to speaking activity from the written text helps to produce the target text at a high level.

Abstract: Automatic Speech Recognition System (ASRS) is not a new concept; however it is an uncharted piece of technology when applied in the process of translation. Serving as a technology that enables the recognition and translation of spoken language into text by computers, ASRS can optimize the time-consuming translation process. To test the hypothesis a two-cycle experiment was carried out with a group of professional translators attempting to explore the quality of the target text and their time spent translating in a nonstandard setting. Experiment Cycle 1 aims to explore if there would be any difference in cognitive processes of the translator while being an interpreter and expressing orally what is in a written text. Design of Cycle 2 concerns the post-editing stage, and provides information about lexical, grammar, syntax and punctuation corrections made by the translator while adopting the text produced by the ASRS. The researcher made use of a user-friendly screen-voice recording software to record every word of the verbalization while sight translation included every change the interpreter made to the rendition; observing the text’s linguistics and translation transformations; looking into the justifications of mental operations made by the translator. The results of this study have some implications for the translation process: 1) the syntax analysis shows that in most cases the translators managed to produce natural word order in target sentences; switching to speaking activity from the written text helps to produce the target text at a high level; 2) the lexical analysis finds mistakes in decoding some lexemes with related pronunciation, mistakes in decoding case flexions, using single instead of plural nouns, tautology, functional styles mixture etc., but if the process is regulated, it will be a promising investment in terms of time and effort; 3) the experience of using speech recognition technology seems to reinforce the translators’ motivation to upgrade their working tools; 4) ASRS serves as a helpful tool for learners to reflect on their rendition processes and develop a set of measures to remedy the mistakes and shortcomings.