A Computer-Assisted Interpreting System for Multilingual Conferences Based on Automatic Speech Recognition
Jichao Liu, C. N. Liu, Buzheng Shan, Ömer S. Ganiyusufoglu
Abstract
Computer-aided interpreting(CAI) systems are software applied to one or more stages of interpreting tasks, which can directly promote the work of interpreters and improve the interpreting quality. So far, there are few researches on CAI tools in simultaneous interpretation, and they are all designed and developed by manual extraction model. There is no study focusing on the implementation of a real CAI tool for automatic extraction of terms, numbers, etc.. Based on the experimental research of existing CAI models, this study puts forward some new methods based on automatic speech recognition(ASR) and develops a CAI system--InterpretSIMPLE with user-friendly interface, which implements automatic retrieval and display of terms (pre-imported), numbers, etc. Through the setting of three-line label control and underline panel control, the system realizes the attention allocation and positioning of the source text content at different levels. One-click import of commonly used Excel glossary gives simple operation with no additional format conversion. Terminologies and their translations and numbers are displayed below the corresponding position while displaying the source text, so that interpreters could locate and solve these recognized SI difficulties. Through the “exact matching” / “partial matching” setting, it could meet the personalized requirements of terms matching. The experiment shows that after the system receives text information from Tencent Cloud, the real-time display rate of the pre-imported glossary reaches 98.92%, and the display rate of numbers is 100%. The research results could provide references for the research and development of in-process CAI tools.