The Impact Of Speech Recognition Software On C-E Simultaneous Interpreting Based On Gile's Effort Model

The rapid development of machine translation and speech recognition technologies in recent decades has helped interpreters ease their burden,especially in simultaneous interpretation which requires multiple skills.However,based on the performance of machine translation and speech recognition systems in real working scenarios,it was found that various obstacles that current technologies face may hinder interpreters' performance.The effort model put forward by Daniel Gile illustrates that interpreters' efforts are coordinated and divided to several parts,including listening and analysis effort,short-term memory effort,speech production effort,and coordination effort.Based on the previous studies,interpreters' pressure can be reduced with the help of speech recognition,as they pay less attention to listening to the source language and short-term memory so that they can be more focused on the language output.However,the current technologies still face a number of obstacles,such as the inability of reorganize the information to achieve precise translation,which may pose challenges to interpreters,or even overload the effort coordination.Whether speech recognition technology serves as a helper or hinderance to interpreters' efforts allocation is still yet to be further observed and studied.With the aim of observing and studying the impact of speech recognition software on interpreters' overall performance in Chinese-English simultaneous interpretation,the author used the combined methodologies of both quantitative and qualitative analysis.The author divided eight participants into two groups,namely the experimental group and the control group.During the experiment,participants of the experimental group were provided with the text converted by speech recognition software,while the control group were required to finish their interpreting process without the help of speech recognition technology.By studying data collected during the experiment,the author found out that speech recognition technology has brought both positive and negative impacts on interpreters' performance.With the help of speech recognition software,interpreters were able to translate more accurately,especially when translating multiple numbers.Meanwhile,it was shown that more efforts were focused on reading the transcript during the experiment,and interpreters have adopted certain strategies in order to achieve greater performance.