Research And Development Of Speech Control System Of Nursing Beds Combined With Voiceprint Recognition

With the seriousness of the aging of the population and the youth of cardiovascular and cerebrovascular diseases, more and more people lose the ability to act, besides, with the lack of the nursing staff, more intelligent care bed need to be developed by society. Care beds controlled by speech instead of a simple button, can bring great convenience for patients with disability. However, in gerocomium and hospitals, there are usually more than one care bed in the same room, and the environment is relatively noisy, it is easy to interfere with each other if many people send speech commands at the same time. If the non-specific human speech control system is applied, anyone can control care bed by sending speech commands, this would have a serious impact on the safety of the patients, and it is possible to cause secondary damage to the patients, which restricts the popularization and application of care bed. To solve this problem, this paper developed a set of speech control system of care bed that have the function of voiceprint recognition based on Android platform.First of all, this paper reviews the background and significance of the research of this topic and the development status quo of care bed, and analyzes the development status quo of voiceprint recognition and speech recognition. The paper points out that control system of care bed that can recognize the characteristics of voiceprint of a particular patient is lacking in the current market, although the processing and recognition technology of speech signal has been quite mature so far.Secondly, Android development platform is selected based on the experience of user with the analyses of the demand of voice control system of care bed and comparison of various development platforms, and then summary design of the speech control system is made.Then, the paper discusses the characteristics of the common audio format, and the experiment of speech recognition is carried out with WAV format on the Android platform, then the data of the audio file extracted is analyzed, and the method of the determination of the parameters is studied. And then the speech data were extracted by Mel transform coefficients (MFCC). At the end of this chapter, the method of feature extraction of MFCC is realized on the Android platform, and the solution to the problem of NaN data is put forward when the program is designed.And then, various algorithms about voiceprint recognition and speech recognition are studied, and GMM is selected as the algorithm of voiceprint recognition. The paper makes experiment validation on Matlab, and chooses the HMM and DTW algorithms as a comparison. And the paper adopts MFCC feature extracted by individual recorded voice as the experimental samples. The experiments have proved that GMM algorithm used for shielding non-care bed user’s voice is suitable for voiceprint recognition of control system under the premise of setting the threshold value reasonably. It is also proved that the recognition effect and the recognition time of the DTW are better than that of the HMM in the case of a small number of training samples and the identification of the isolated words. At the end of this chapter, the algorithms of GMM and DTW are also implemented on the Android platform, and the problem and method of processing of covariance matrix approximation "strange" is proposed in the GMM program design.Then, according to the summary design, starting from with the interface and program, this paper expounds the design process of care bed control system of speech in two aspects on the Android platform, after that, making performance tests on speech control system that have being realized. After setting the threshold value, when the recall rate of voiceprint recognition is 72.5%, speech of non-care bed users has a probability of 1.25% of causing a care bed action. After voiceprint recognition, speech recognition rate of care bed users is 97.13%, however, speech recognition rate of the non-care bed users is 14.29%.At last, the paper makes the summaries and prospects of this project, and puts forward the direction of the subject in the future.