MEDICAL TRANSCRIPTION USING SPEECH RECOGNIZER

  • Mahidhar B V S
Keywords: Speaker Recognition; Sub region Model; Model Synthesis.

Abstract

Speech recognition is a vital part in medical transcriptions. The existing speech recognition systems that run as standalone desktop applications fall short in many cases due to low accuracy rates and high processing time. This paper proposes a novel collaborative approach for the automation of speech to text conversion. The model proposed leverages the power of cloud computing and the unique nature of computing. This framework has many real time applications such as in Medical Transcription systems, IVR systems etc., The generic framework here is advantageous, because the speech models in Automatic Speech Recognizer (ASR) could be trained according to specific domain required, allowing wide usability. The proposed speech framework is used for medical transcription process which is automated by using the proposed speech framework. With this system, an android application was developed which acts as a medium between doctors and their patients. The application helps diagnose the patients using their symptoms. The doctors prescribe medicines through this
application to patients for various kinds of illness. It is user friendly and secure as it can be used by anyone round the clock. The entire model is developed for a mobile cloud environment considering the characteristics of cloud delivery models.

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Author Biography

Mahidhar B V S

Department of Computer Science Engineering, SRM University, Ramapuram, Chennai – 89

References

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Published
2017-03-27
Section
Articles