Study On The Application Of The Distributed Speech Recognition In Radiology Information System

At present, the hospital information construction in China has entered into the digital stage. The medical information system is extensively applied, the main purpose of which is to better take advantage of patient diagnostic information and to improve the transmission speed of inspection information, thereby increasing the utilization of hospital resources. Apparently, the medical image diagnostic information is one of the most important sources of medical information.As the key communication medium between Radiologist and related clinical radiologist, the medical image diagnostic reports must be generated timely and accurately. However, in the diagnostic process, the radiologist needs to focus on the medical image analysis, which leads to the diagnostic report cannot be made in real time. In order to provide timely and accurate diagnosis and treatment for some special occasion, such as the emergency, the medical diagnostic report must be completed within a limited time. Therefore, the modern computer information technology must be applied to break through the limitations of traditional medical report or record input mode. Currently, speech recognition technology has become more sophisticated, and it is highly likely to become the main human-computer interaction method of the next generation operating system. Introducing speech recognition technology into the entry process of the radiology diagnostic imaging report, will greatly reduce the time doctors make a diagnosis. Overall, it will improve hospitals'abilities of receiving and treating patients, while greatly reducing the valid waiting time for patients and increasing their satisfactions. This thesis designs and implements a specialized distributed speech recognition system used in generating radiology diagnostic imaging reports. Firsty, the paper discusses related key technologies of the distributed speech recognition, including the core idea of HMM and basic algorithms. The author illustrates further information on the front-end distributed speech recognition system involved in speech endpoint detection, parameter extraction technology, voice data transmission protocol between the client and server-side as well as the major server search and identify technology. Secondly, the distributed speech recognition system designed in radiology information systems is given in detail, including the system requirements analysis, setting up the system overall framework and designing front-end voice and data processing module, voice characteristics of data transmission module and server-side speech recognition module. Finally, a distributed speech recognition system in radiology information system is accomplished, and the experimental results are analyzed. The results show that in the laboratory environmental conditions, the recognition effect of speech recognition system dedicated to a specific person's entry about Radiology Imaging Reporting is relatively ideal, and it's comparable with the effect of IBM Viavoice 9.1 system.