What is Model Talker?

Markov Model is a statistical model widely used in various natural language processing applications such as speech recognition, automatic part-of-speech tagging, phonetic conversion, and probabilistic grammar. After long-term development, especially the successful application in speech recognition, it has become a general statistical tool.

Markov model

Markov is a representative of the Petersburg school of mathematics. Number theory and

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Mainly used in speech recognition, phonetic conversion, part-of-speech tagging.

Natural language is a tool for humans to communicate information. Many natural language processing problems can be equated with decoding problems in communication systems-a person guesses what the speaker wants to say based on the information received. This is actually like communication, people analyze, understand, and restore the information transmitted by the sender based on the signal received by the receiver. For example, in a typical communication system: where s1, s2, s3 ... represent signals from information sources. o1, o2, o3 ... are the signals received by the receiver. The decoding in communication is to restore the sent signals s1, s2, s3 ... according to the received signals o1, o2, o3 ....

In fact, when people talk, their brains are the same.

In the introduction of human resource management, Markov model is a dynamic prediction technology used to predict the distribution of various types of personnel at equal time intervals (usually one year). It is a quantitative prediction borrowed from statistics. method. Its basic idea is: find out the proportion of human resource flow in the past, and use it to predict the future situation of human resource supply.

The number of people transferred from a lower level to a higher level within a given period of time, or the number of people transferred from one type to another type is a proportion of the total number of low-level people or the total number of people of a type at the beginning. For personnel transfer rate.