9. A speech recognition system based on user personalized information, comprising: a memory; and a processing device, communicatively coupled to the memory, to: receive a speech signal; decode the speech signal according to a basic static decoding network to obtain a decoding path on each active node in the basic static decoding network, wherein the basic static decoding network is formed by extending words in a basic name language model into corresponding acoustic units, and wherein the basic name language model comprises a first statistical probability between two common words and a second statistical probability between a common word and a name; generate a user-specific name language model comprising a third statistical probability between the name and a user identifier; build an affiliated static decoding network associated with the user-specific name language model by extending words in the user-specific name language model into corresponding acoustic units, wherein to build the affiliated static decoding network, the processing device is further to: set a first pronunciation of a first word at a beginning of a sentence in the user-specific name language model to a first virtual pronunciation; set a second pronunciation of a second word at an end of the sentence in the user-specific name language model to a second virtual pronunciation; and extend a special pronunciation unit on an outgoing arc of a node corresponding to the beginning of the sentence and an incoming arc of the node corresponding to the end of the sentence to obtain the affiliated static decoding network associated with the user-specific name language model; and responsive to identifying that a decoding path enters a name node in the basic static decoding network, extend an extra network associated with the name node according to the affiliated static decoding network; and return a recognition result after the decoding is completed, wherein a recognition accuracy rate for names is improved.
9. A speech recognition system based on user personalized information, comprising: a memory; and a processing device, communicatively coupled to the memory, to: receive a speech signal; decode the speech signal according to a basic static decoding network to obtain a decoding path on each active node in the basic static decoding network, wherein the basic static decoding network is formed by extending words in a basic name language model into corresponding acoustic units, and wherein the basic name language model comprises a first statistical probability between two common words and a second statistical probability between a common word and a name; generate a user-specific name language model comprising a third statistical probability between the name and a user identifier; build an affiliated static decoding network associated with the user-specific name language model by extending words in the user-specific name language model into corresponding acoustic units, wherein to build the affiliated static decoding network, the processing device is further to: set a first pronunciation of a first word at a beginning of a sentence in the user-specific name language model to a first virtual pronunciation; set a second pronunciation of a second word at an end of the sentence in the user-specific name language model to a second virtual pronunciation; and extend a special pronunciation unit on an outgoing arc of a node corresponding to the beginning of the sentence and an incoming arc of the node corresponding to the end of the sentence to obtain the affiliated static decoding network associated with the user-specific name language model; and responsive to identifying that a decoding path enters a name node in the basic static decoding network, extend an extra network associated with the name node according to the affiliated static decoding network; and return a recognition result after the decoding is completed, wherein a recognition accuracy rate for names is improved. 12. The system according to claim 9 , wherein the processing device is further to: generate the basic name language model; and build the basic static decoding network associated with the basic name language model.