Automatic audio announcement systems are widely used in public places such as transportation vehicles and facilities, hospitals, and\nbanks. However, these systems cannot be used by people with hearing impairment. That brings great inconvenience to their lives.\nIn this paper, an approach of audio announcement detection and recognition for the hearing-impaired people based on the smart\nphone is proposed and a mobile phone application (app) is developed, taking the bank as amajor applying scenario. Using the app,\nthe users can sign up alerts for their numbers and then the system begins to detect audio announcements using the microphone\non the smart phone. For each audio announcement detected, the speech within it is recognized and the text is displayed on the\nscreen of the phone. When the number the user input is announced, alert will be given by vibration. For audio announcement\ndetection, a method based on audio segment classification and postprocessing is proposed, which uses a SVM classifier trained\non audio announcements and environment noise collected in banks. For announcement speech recognition, an ASR engine is\ndeveloped using a GMM-HMM-based acoustic model and a finite state transducer (FST) based grammar. The acoustic model is\ntrained on audio announcement speech collected in banks, and the grammar is human-defined according to the patterns used\nby the automatic audio announcement systems. Experimental results show that character error rates (CERs) around 5% can be\nachieved for the announcement speech, which shows feasibility of the proposed method and system.
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