An Empirical Study On How Voice Recognition Technology Influences Chinese-English Simultaneous Interpretation Of Numbers

Voice recognition technology is witnessing rising recognition accuracy.The technology,if capable of increasing accuracy in number interpretation,could be instrumental to interpreters.Guided by Gile's Effort Models,this thesis aims to delve into the following questions: during Chinese-English simultaneous interpretation,whether Xunfei,a voice recognition app,helps interpreters translate numbers more accurately and fluently;to what kinds of numbers Xunfei gives the strongest boost;if it helps with the interpretation of units;and if recognition errors and delays set back interpreters.The thesis chooses 2 materials,each containing 25 numbers,for the experiment.The first material is about climate change and the second about Canton Fair.15 participants need to interpret the first material without Xunfei's assistance and the second the otherwise.The voice recognition process is made into a video on iPad mini4 to facilitate the experiment process.The result shows that the voice recognition technology indeed helps increase interpreters' number accuracy as it enables interpreters to more accurately translate numbers concerning years,percentages and large digits.The most palpable progress lies in percentage interpretation.And it doesn't help interpreters as much in coping with number misses as in increasing number accuracy;It is a mixed picture for fluency analysis,because the participants paused longer,reduced repeats and fillers whereas increased modifications;IFLYTEK also marginally boosted the participants' performance in interpreting units and drastically enhanced their performances in interpreting descriptive information.On the flip side,inaccurate recognition of 20% numbers undermines interpreters' ability to accurately interpret numbers;Xunfei also negatively affected their performances because of delays in voice recognition.