Study Of Vehicle Navigation With Speech Recognition

As a new concept, the application of GPS and navigation are widely introduced into the field of commercial technology. This is an application of space technology, and anyone could get his/her specific location and the speed. GPS which was first invented in US Department of Defense and used in army has been open gradually from 1984, also were used in civilian equipment. In the 21st century GPS has been applied in many aspects such as vehicle navigation and measuring precision instruments largely. Now with the increasing sophisticated of highway traffic the number of car ownership is growing, the need of learning the car’s location, traffic map and other information for drivers is also expanded. Meanwhile as the increasing demand of positioning equipment of the vehicle navigation itself, a wide variety of vehicle navigation were invented in the market gradually. When there is the equipment of vehicle navigation in the car, the driver could drive in all strange city and dense highway freely by the equipment, and don’t worry about finding the destination. But importing the equipment of vehicle navigation’s information totally depends on manual operation, the information received will be disposed through navigation system and then the equipment will give the appropriate driving directions. However, they almost were hurry on the road for the drivers, operating the equipment while driving will bring the drivers a lot of security risks. So introducing speech recognition technology into vehicle navigation equipment will remove these risks ,the drivers need not put their hands away from the steering, they can operate the equipment through voice command, the whole process will become more safe and convenient. This is also the goal of the study.This paper describes the subject’s purpose and meaning, the development and status of speech recognition and vehicle navigation, and also introduces the design of this paper. First, this paper introduces the basic principles and research methods of the speech recognition technology in theory, selects Hidden Markov Model as the thesis of basic recognition algorithm. Secondly in terms of hardware, chose a processor ARM9 with S3C2410 as an experimental platform, and transplants embedded Linux systems, as well as external device hardware driver. Finally, simulates the results using Hidden Markov Model Toolkit on speech recognition, received a series of experimental data.