TECHNICAL FIELD

The present application relates to the field of audio processing, in particular to a method and device for recognizing the state of a meridian.

BACKGROUND ART

As everyone knows, the five internal organs (spleen, lung, liver, heart and kidney) of a human body respectively correspond to the five pitches (Gong, Shang, Jue, Zhi and Yu (respectively equivalent to do, re, mi, sol and la)) in classical music. Each one of the five pitches is subdivided into five tones, forming 25 musical scales corresponding to the states of 25 viscera and meridians. “Five Zang-organs harmonize pitch”, as a basis for determining the state of a meridian, can prompt what kind of meridian and dietary conditioning should be performed to finally achieve the purpose of performing physiological conditioning and evaluation on an acquired parameter.

However, conventional voice classification is completely dependent on expert experience, which is difficult and has a high individual requirement for a subject. With the development of the voice signal processing technology and the mode recognition technology, how to utilize the voice recognition technology to classify the state of a human body meridian is a problem urgent to be solved in the art.

The information disclosed in the background art part of the present application is only intended to deepen the understanding to the common background art of the present application, but shall not be deemed to admit or imply in any form that the information forms commonly known prior art for a person skilled in the art.

SUMMARY OF THE INVENTION

The main object of the present application is to provide a method and device for recognizing the state of a human body meridian by utilizing a voice recognition technology.

In order to solve the above-described problem, the present application relates to a method for recognizing the state of a meridian, the method comprising: receiving an input voice of a user; preprocessing the input voice; extracting a stable feature of the preprocessed input voice; primarily classifying the stable feature on the basis of a feature recognition model, and determining a basic classification pitch, wherein the basic classification pitch comprises Gong, Shang, Jue, Zhi and Yu (respectively equivalent to do, re, mi, sol and la); secondarily classifying the stable feature on the basis of the feature recognition model, and determining a secondary classification tone in the basic classification pitch; and recognizing the state of a meridian according to the secondary classification tone.

Further, the step of receiving an input voice of a user comprises: sequentially displaying first to fifth prompt words and starting to receive first to fifth input voices of a user; after the first to fifth input voices of the user are received, recognizing the received first to fifth input voices to be first to fifth user words; respectively comparing the first to fifth user words with the first to fifth prompt words; and integrating the user words matched with the prompt words to be an audio file as the input voice.

Still further, the first to fifth prompt words can respectively be: “do”, “re”, “mi”, “sol” and “la”.

Further, the step of preprocessing the input voice comprises: performing noise reduction on the input voice, and performing voice signal pre-emphasis on the noise-reduced input voice.

Still further, the noise reduction process comprises: removing background noise and current noise in the input voice; and the voice signal pre-emphasis comprises: improving a high frequency voice signal.

Further, the step of extracting a stable feature of the preprocessed input voice may comprise: transforming the sequence of the input voice into a frequency domain feature through Fourier transform to obtain a signal power spectrum; utilizing discrete cosine transform to remove the correlation between signal dimensions to obtain a 24-dimensional feature of a sample; and utilizing a manifold learning method to reduce the 24-dimensional feature to be a 12-dimensional feature to obtain the stable feature.

Further, the step of establishing a feature recognition model comprises: establishing a directed Gaussian mixture graphical model for the basic classification pitch; and utilizing a Bayesian graphical learning algorithm to train the directed Gaussian mixture graphical model.

The present application further relates to a device for recognizing the state of a meridian, the device comprising: a receiving module, for receiving an input voice of a user; a preprocessing module, for preprocessing the input voice; an extraction module, for extracting a stable feature of the preprocessed input voice; a primary classification module, for primarily classifying the stable feature on the basis of a feature recognition model, and determining a basic classification pitch, wherein the basic classification pitch comprises Gong, Shang, Jue, Zhi and Yu (respectively equivalent to do, re, mi, sol and la); a secondary classification module, for secondarily classifying the stable feature on the basis of the feature recognition model, and determining a secondary classification tone in the basic classification pitch; and a determination module, for recognizing the state of a meridian according to the secondary classification tone.

In addition, the present application further relates to a mobile device, comprising a memory, a processor and a program stored in the memory and capable of running on the processor, wherein the steps of the method for recognizing the state of a meridian as described above can be realized when the processor executes the program.

Further, the mobile device may comprise a tablet computer, a notebook, a mobile desktop computer and/or a mobile phone.

The beneficial effects of the present application are: the method for recognizing the state of a human body meridian of the present invention can accurately recognize the state of a human body meridian by classifying individual voices, and solves the problem that conventional voice recognition and classification are completely dependent on human experience. The method for recognizing the state of a human body meridian of the present invention utilizes the voice signal processing technology and the mode recognition technology, uses modern technologies to classify a voice signal and determine the state of an individual body, and can reduce the dependence of individual voice classification on professional experience, thus having a positive effect.

