A Computer-Assisted Interpreting System for Multilingual Conferences Based on Automatic Speech Recognition

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. Until now, studies on CAI in simultaneous interpretation(SI) have been limited, primarily focusing on the design and development of manual extraction models. Moreover, what’s particularly noteworthy is the lack of thorough investigation into the development of fully automated CAI models for extracting terms (SI difficulties) and other related aspects. Based on the experimental research of existing ones, 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. as well as other functions specialized for conference interpreters. 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 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” or “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%. The research results could provide references for the research and development of in-process automated CAI tools.

Keywords

• Computer-aided interpreting
• CAI
• simultaneous interpreting
• automatic speech recognition
• artificial intelligence