CN109726392A - A kind of intelligent language Cognitive Information Processing Based and method based on big data - Google Patents
A kind of intelligent language Cognitive Information Processing Based and method based on big data Download PDFInfo
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- CN109726392A CN109726392A CN201811521939.7A CN201811521939A CN109726392A CN 109726392 A CN109726392 A CN 109726392A CN 201811521939 A CN201811521939 A CN 201811521939A CN 109726392 A CN109726392 A CN 109726392A
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Abstract
The invention belongs to big data fields, disclose a kind of intelligent language Cognitive Information Processing Based and method based on big data；Language is inputted with text input form by voice；Word extraction is carried out using best uniformity approximation method to language using word, Chinese idiom, proverb, sentence pattern, word is converted after extracting；To conversion content and Installed System Memory sentence anticipate, checked using Xiao Weinie algorithm, to conversion content verify；By being input to microprocessor after verifying；Extraction and conversion are re-started after authentication failed, are entered and left after qualified and are arrived microprocessor；Finally information save and export by loudspeaker using the wavelet field denoising of PURE-LET.The present invention can make the error rate of intelligent language cognitive system substantially reduce, and can carry out multilingual conversion, and transformation efficiency can be improved by memory function.
Description
Technical field
The invention belongs to big data field more particularly to a kind of intelligent language Cognitive Information Processing Baseds based on big data
And method.
Background technique
Language is just to instruct meeting using a set of communication instruction for having and being jointly processed by rule to be expressed in the broadest sense
It is transmitted with vision, sound or tactile manner.Strictly speaking, language refers to instruction used in human communication-nature language
Speech.Owner is by learning the language competence to obtain, and the purpose of language is exchange idea, opinion, thought etc..Language
Learn be exactly from human research's language classification with it is regular and developed.Language is a kind of interpersonal exchange way, people
It is mutual associate be unable to do without language.Although can transmit the thought of people by picture, movement, expression etc., language is
The medium of most important one and most convenient.When the mankind have found that certain animals can link up in some way, with regard to being born
The concept of animal language.The birth of computer is arrived, human needs give computer instruction.It is this " unidirectional to link up " just at computer language
Speech.But computer can not recognize well when directly understanding the language that the mankind say, computer is recognized in intelligent language at present
Know that aspect error rate is high, and there are many words that can not identify, simple single identification can only be carried out.
In conclusion problem of the existing technology is:
Computer error rate in terms of intelligent language cognition is high at present, and has many words that can not identify, can only carry out
Simple single identification.
It can not accurately be extracted to word in the prior art；Conversion content cannot be removed effectively mistake in the prior art
Accidentally or unnecessary information, extension proof time reduce verification efficiency, cannot achieve the efficient verification to conversion content；The prior art
Interference of the middle information vulnerable to extraneous factor reduces information quality, causes error, and it is accurately defeated to be unfavorable for loudspeaker progress
Out.
Summary of the invention
In view of the problems of the existing technology, at the intelligent language cognitive information based on big data that the present invention provides a kind of
Manage system and method.
The invention is realized in this way a kind of intelligent language method for processing cognitive information based on big data, described to be based on
The intelligent language method for processing cognitive information of big data includes:
The first step is inputted language with text input form by voice；
Second step carries out word extraction using best uniformity approximation method to language using word, Chinese idiom, proverb, sentence pattern,
Word is converted after extracting；
Third step, to conversion content and Installed System Memory sentence anticipate, checked using Xiao Weinie algorithm, to conversion content
It is verified；
4th step, by being input to microprocessor after verifying；Extraction and conversion are re-started after authentication failed, are gone out after qualified
Enter to microprocessor；Finally information save and export by loudspeaker using the wavelet field denoising of PURE-LET.
Further, best uniformity approximation side is used for language using word, Chinese idiom, proverb, sentence pattern in the second step
Method carries out word extraction, specific algorithm are as follows: f (x) ∈ C [a, b], pn(x) collection that all multinomials for being number no more than n are constituted
It closes；If:
Then claiming p* (x) is optimal and uniform approximating polynomial of the f (x) on [a, b], also referred to as the very big multinomial of minimization；
Optimum polynomial is sought using Li meter Zi algorithm；It is solved according to chebyshev's theorem:
Wherein: ak (k=0,1 ... it n) is multinomial coefficient to be asked；ρ is most preferably to approach value；xiIt is obtained with correction method repeatedly.
Further, conversion content is checked in the third step using Xiao Weinie algorithm, is realized to conversion content
Efficient verification；With algorithm are as follows:
Utilize data sample set S0={ x0, x1..., xn, m error information sample point, f are contained in n sample data0
It (x) is the function for reflecting this group of data sample essential characteristic, as follows:
In formula: n is the number of individuals of one group of data；
Di=| xi-f(xi)|；
For measuring sample points according to xiThe degree of deflection function relationship, DiBigger, sample point becomes the possibility of error information
Property is bigger；D is asked to n dataiMaximum value；
Xiao Weinie algorithm rejects DiIt is worth maximum sample point j, establishes new sample set S1={ S0–xj, to remaining number
According to repetitive operation is carried out, when data meet operation termination condition, m sample point of rejecting is exactly error information.
Another object of the present invention is to provide the intelligent language cognitive information processing described in a kind of realize based on big data
The intelligent language Cognitive Information Processing Based based on big data of method, at the intelligent language cognitive information based on big data
Reason system include: language receiving module, text input module, word extraction module, conversion module, authentication module, microprocessor,
Storage module, loudspeaker module, big data；
Big data provides knowledge and supports to word extraction module, authentication module；Speech reception module and text input module
It is extracted, will be converted after word extraction module by word extraction module after being inputted, conversion module will be in conversion
Appearance is input to authentication module；
Authentication module is input to microprocessor after being verified, return to word extraction module after authentication failed and turned again
Change；
Microprocessor will convert information preservation to storage module；Microprocessor carries out information by loudspeaker module defeated
Out.
Another object of the present invention is to provide the intelligent language cognitive information processing described in a kind of application based on big data
The remaining metacognition platform of method.
Advantages of the present invention and good effect are as follows: be provided with authentication module, the information that authentication module exports conversion module
It is verified with information in big data, if examining conversion wrong, re-starts extraction conversion, system is had correctly
Cognition, avoids mistake；The invention is provided with storage module, and storage module can record the language after conversion, in turn
So that conversion system generates memory, so that more rapid when conversion next time.The invention is provided with big data, can make system
Vocabulary source it is more wide, can identify multilingual, common saying Chinese idiom etc. can be inquired, error rate is low.It can make intelligence
The error rate of energy language acknowledging system substantially reduces, and can carry out multilingual conversion, can be improved by memory function
Transformation efficiency.
The present invention carries out word using best uniformity approximation method for language using word, Chinese idiom, proverb, sentence pattern etc. and mentions
It takes, improves the accuracy that word extracts；The present invention checks conversion content using Xiao Weinie algorithm, effectively remove mistake or
Unnecessary information improves verification efficiency, realizes the efficient verification to conversion content；The present invention is to information using the small of PURE-LET
Curvelet domain denoising is saved, and the interference of extraneous factor is effectively avoided, and guarantees information quality, and it is accurate to be conducive to loudspeaker progress
Output.
Detailed description of the invention
Fig. 1 is the intelligent language method for processing cognitive information flow chart provided in an embodiment of the present invention based on big data.
Fig. 2 is the intelligent language Cognitive Information Processing Based structural representation provided in an embodiment of the present invention based on big data
Figure；
In figure: 1, language receiving module；2, text input module；3, word extraction module；4, conversion module；5, mould is verified
Block；6, microprocessor；7, storage module；8, loudspeaker module；9, big data.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
1 detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, the intelligent language method for processing cognitive information provided in an embodiment of the present invention based on big data, specifically
The following steps are included:
S101: language is inputted with text input form by voice；
S102: word is carried out using best uniformity approximation method for language using word, Chinese idiom, proverb, sentence pattern etc. and is mentioned
It takes, word is converted after extracting；
S103: to conversion content and Installed System Memory sentence anticipate, checked using Xiao Weinie algorithm, to conversion content into
Row verifying；
S104: by being input to microprocessor after verifying；Extraction and conversion are re-started after authentication failed, are entered and left after qualified
To microprocessor；Finally information save and export by loudspeaker using the wavelet field denoising of PURE-LET.
It is provided in an embodiment of the present invention that language is used most using word, Chinese idiom, proverb, sentence pattern etc. in step S102
Good Uniform approximat method carries out word extraction, improves the accuracy that word extracts；Specific algorithm are as follows:
If f (x) ∈ C [a, b], pn(x) set that all multinomials for being number no more than n are constituted；If
Then claiming p* (x) is optimal and uniform approximating polynomial of the f (x) on [a, b], also referred to as the very big multinomial of minimization；
Optimum polynomial is sought using Li meter Zi algorithm；It is solved according to chebyshev's theorem
Wherein: ak (k=0,1 ... it n) is multinomial coefficient to be asked；ρ is most preferably to approach value；xiIt is obtained with correction method repeatedly.
It is provided in an embodiment of the present invention that conversion content is checked using Xiao Weinie algorithm in step S103, effectively go
Except mistake or unnecessary information, verification efficiency is improved, realizes the efficient verification to conversion content；With algorithm are as follows:
Utilize data sample set S0={ x0, x1..., xn, m error information sample is contained in n sample data
Point, f0It (x) is the function for reflecting this group of data sample essential characteristic, as follows:
In formula: n is the number of individuals of one group of data；
Di=| xi-f(xi)|
For measuring sample points according to xiThe degree of deflection function relationship, DiBigger, sample point becomes the possibility of error information
Property is bigger；D is asked to n dataiMaximum value；
Xiao Weinie algorithm rejects DiIt is worth maximum sample point j, establishes new sample set S1={ S0-xj, to remaining number
According to repetitive operation is carried out, when data meet operation termination condition, m sample point of rejecting is exactly error information.
It is provided in an embodiment of the present invention that information is saved using the wavelet field denoising of PURE-LET in step S103,
The interference of extraneous factor is effectively avoided, guarantees information quality, is conducive to loudspeaker and is accurately exported；Specific algorithm
Are as follows:
Information under each scale estimates wavelet coefficientWrite as one group of basic threshold function table
Linear combination:
And coefficient vector a=[a is determined by the minimum of PURE1..., aM]T；
Enable θ (d, s)=θj(di, sj) it is noiseless wavelet coefficient δ=δjOne estimation；Function #+(d, s) and θ-(d, s)
It is as follows:
Wherein,ForStandard base, remove ek(k)=outer remaining element is 0；Then stochastic variable PUREjFor
The unbiased esti-mator of MSE under subband j, i.e. E { PUREj}=E { MSEj}；
By the minimum of PURE, carry out the linear combination parameter of wavelet estimators in calculating formula (2)；Formula (2) are substituted into formula
(3), it and omits independent variable (d, s), has
As shown in Fig. 2, the intelligent language Cognitive Information Processing Based provided in an embodiment of the present invention based on big data, specifically
Include:
Language receiving module 1, text input module 2, word extraction module 3, conversion module 4, authentication module 5, micro process
Device 6, storage module 7, loudspeaker module 8, big data 9.
Big data 9 provides knowledge to word extraction module 3, authentication module 4 and supports；Speech reception module 1 and text are defeated
Enter and extracted after module 2 is inputted by word extraction module 3, will be converted after word extraction module 3, conversion module
Conversion content is input to authentication module 5 by 4.
Authentication module 5 provided in an embodiment of the present invention is input to microprocessor 6 after being verified, return to word after authentication failed
Language extracts 3 pieces of mould and is converted again.
Microprocessor 6 provided in an embodiment of the present invention will convert information preservation to storage module 7.
Microprocessor 6 provided in an embodiment of the present invention exports information by loudspeaker module 8.
The working principle of the invention: being inputted by speech reception module 1 and text input module 2, and word extracts mould
Block 3 is extracted by word, Chinese idiom, proverb, the sentence pattern etc. in big data 9, and word carries out after extracting by 4 turns of conversion module
Change, conversion content is input to authentication module 5 and is verified, authentication module 5 receives existing sentence meaning in big data 9 and carries out core
Right, authentication module 5 is input to microprocessor 6 after being verified, and returns to word extraction module 3 after authentication failed and converts extracting mode
Again it is converted, microprocessor 6 is exported by information preservation to storage module 7 and by loudspeaker module 8.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. a kind of intelligent language method for processing cognitive information based on big data, which is characterized in that the intelligence based on big data
Can language acknowledging information processing method include:
The first step is inputted language with text input form by voice；
Second step carries out word extraction, word using best uniformity approximation method to language using word, Chinese idiom, proverb, sentence pattern
It is converted after extraction；
Third step, to conversion content and Installed System Memory sentence anticipate, checked using Xiao Weinie algorithm, to conversion content carry out
Verifying；
4th step, by being input to microprocessor after verifying；Extraction and conversion are re-started after authentication failed, are entered and left and are arrived after qualified
Microprocessor；Finally information save and export by loudspeaker using the wavelet field denoising of PURE-LET.
2. the intelligent language method for processing cognitive information based on big data as described in claim 1, which is characterized in that described
Word extraction is carried out using best uniformity approximation method for language using word, Chinese idiom, proverb, sentence pattern in two steps, it is specific to calculate
Method are as follows: f (x) ∈ C [a, b], pn(x) set that all multinomials for being number no more than n are constituted；If:
Then claiming p* (x) is optimal and uniform approximating polynomial of the f (x) on [a, b], also referred to as the very big multinomial of minimization；
Optimum polynomial is sought using Li meter Zi algorithm；It is solved according to chebyshev's theorem:
Wherein: ak (k=0,1 ... it n) is multinomial coefficient to be asked；ρ is most preferably to approach value；xiIt is obtained with correction method repeatedly.
3. the intelligent language method for processing cognitive information based on big data as described in claim 1, which is characterized in that described
Conversion content is checked using Xiao Weinie algorithm in three steps, realizes the efficient verification to conversion content；With algorithm are as follows:
Utilize data sample set S0={ x0, x1..., xn, m error information sample point, f are contained in n sample data0(x)
It is the function for reflecting this group of data sample essential characteristic, as follows:
In formula: n is the number of individuals of one group of data；
Di=| xi-f(xi)|；
For measuring sample points according to xiThe degree of deflection function relationship, DiBigger, sample point is got over as a possibility that error information
Greatly；D is asked to n dataiMaximum value；
Xiao Weinie algorithm rejects DiIt is worth maximum sample point j, establishes new sample set S1={ S0–xj, to remaining data into
Row repetitive operation, when data meet operation termination condition, m sample point of rejecting is exactly error information.
4. a kind of intelligent language method for processing cognitive information realized described in claim 1 based on big data based on big data
Intelligent language Cognitive Information Processing Based, which is characterized in that the intelligent language Cognitive Information Processing Based based on big data
It include: language receiving module, text input module, word extraction module, conversion module, authentication module, microprocessor, storage mould
Block, loudspeaker module, big data；
Big data provides knowledge and supports to word extraction module, authentication module；Speech reception module and text input module carry out
It is extracted, will be converted after word extraction module, it is defeated that conversion module will convert content by word extraction module after input
Enter to authentication module；
Authentication module is input to microprocessor after being verified, return to word extraction module after authentication failed and converted again；
Microprocessor will convert information preservation to storage module；Microprocessor exports information by loudspeaker module.
5. a kind of intelligent language method for processing cognitive information using described in claims 1 to 3 any one based on big data
Remaining metacognition platform.
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