CN104978971B - A kind of method and system for evaluating spoken language - Google Patents
A kind of method and system for evaluating spoken language Download PDFInfo
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Abstract
The present invention relates to field of voice signal, disclose a kind of method and system for evaluating spoken language.This method comprises: receiving voice data to be evaluated；It is scored using the first system the voice data, obtains the first appraisal result；If first appraisal result meets first condition, first appraisal result is exported；Otherwise, it is scored using second system the voice data, obtains the second appraisal result；If second appraisal result meets second condition, first appraisal result and second appraisal result are merged, obtain the first fusion appraisal result, then exports the first fusion appraisal result；Otherwise, it is scored using third system the voice data, obtains third appraisal result；First appraisal result, the second appraisal result and third appraisal result are merged, the second fusion appraisal result is obtained, then exports the second fusion appraisal result.The operation efficiency of system is greatly improved on the basis of guaranteeing to evaluate and test precision using the present invention.
Description
Technical field
The present invention relates to field of voice signal, and in particular to a kind of method and system for evaluating spoken language.
Background technique
As the important medium of interpersonal communication, conversational language occupies extremely important status in real life.With society
The aggravation of continuous development and the trend of globalization that can be economic, people to the objectivity of the efficiency of language learning and language assessment,
Fairness and scale test propose increasingly higher demands.Traditional artificial spoken language proficiency evaluating method makes Faculty and Students
Be very limited on instructional blocks of time and space, teacher strength, teaching place, in terms of there is also many hard
Gap and imbalance on part；Artificial evaluation and test not can avoid the individual deviation of evaluator itself, thus it cannot be guaranteed that standards of grading
Unification, can not even accurately reflect the true horizon of measured sometimes；And for extensive oral test, then it needs a large amount of
Human and material resources and financial support limit regular, scale assessment test.For this purpose, industry has developed some languages in succession
It teaches by precept and evaluating system.
For manually scoring is not sufficiently stable under big working strength, or even not fair enough problem, spoken automatic judgment become
Trend of the times.Legacy system, which is used, develops different language teaching and points-scoring system, different scorings based on speech recognition technology
System respectively has advantage because of application environment difference, and for the risk for reducing machine scoring, existing oral evaluation system is frequently with polyphyly
System fusion method, such method is individually evaluated and tested with multiple and different points-scoring systems, then to the score more runs of acquired multisystem
Data are merged, and best result, average mark as described in selection in score are finally scored.Legacy system passes through synthesis
Multisystem scoring, is effectively reduced oral evaluation system and high score data is commented to low risk, but exacerbates calculation resources consumption and comment
Time overhead is surveyed, such as in the integration program using N number of system, oral evaluation total time-consuming will be N times of single system.Especially
Under the limited application environment of calculation resources, evaluation and test efficiency is in urgent need to be improved.
Summary of the invention
The embodiment of the present invention provides a kind of method and system for evaluating spoken language, for mentioning on the basis of guaranteeing to evaluate and test performance
The operation efficiency of high system.
For this purpose, the invention provides the following technical scheme:
A kind of oral evaluation method, comprising:
Receive voice data to be evaluated；
It is scored using the first system the voice data, obtains the first appraisal result；
If first appraisal result meets first condition, first appraisal result is exported；
Otherwise, it is scored using second system the voice data, obtains the second appraisal result；
If second appraisal result meets second condition, first appraisal result and second scoring are tied
Fruit is merged, and the first fusion appraisal result is obtained, and then exports the first fusion appraisal result；
Otherwise, it is scored using third system the voice data, obtains third appraisal result；
First appraisal result, the second appraisal result and third appraisal result are merged, the second fusion is obtained and comments
Divide as a result, then exporting the second fusion appraisal result.
Preferably, the method also includes:
Preset the first system, second system and third system；Or
The first system, second system described in real-time selection and third system.
Preferably, the first system, second system and the third system of presetting includes:
The recognition confidence and evaluation result closed according to dependence test collection, selects the system of best performance as the first system
System；
Select the system complementary with the first system as second system.
Preferably, the first system, second system described in the real-time selection and third system include:
According to system running environment or voice data feature, real-time selection the first system；
Select the system complementary with the first system as second system.
Preferably, the method also includes:
According to different application scenarios and demand, the first condition and second condition are determined.
Preferably, the first condition is that first appraisal result is higher than setting score value；Or the first condition is
The recognition confidence of the first system is higher than setting thresholding.
Preferably, the second condition is that the difference of first appraisal result and second appraisal result is less than setting
Difference.
A kind of oral evaluation system, comprising:
Receiving module, for receiving voice data to be evaluated；
The first system module obtains the first appraisal result for scoring the voice data；
Judgment module, for judging whether first appraisal result meets first condition, if it is, by described first
Appraisal result sends output module to, so that the output module exports first appraisal result；Otherwise, second system is notified
Module scores to the voice data；
The second system module obtains the second appraisal result for scoring the voice data；
The judgment module, is also used to judge whether second appraisal result meets second condition, if it is, notice
First Fusion Module merges first appraisal result and the second appraisal result；Otherwise, third system module pair is notified
The voice data scores；
First Fusion Module, for carrying out fusion to first appraisal result and the second appraisal result and obtaining
One fusion appraisal result sends output module to, so that output module output the first fusion appraisal result；
The third system module obtains third appraisal result for scoring the voice data；
Second Fusion Module, for melting to first appraisal result, the second appraisal result and third appraisal result
Merge the second fusion appraisal result that will be obtained and send the output module to, so that output module output described second is melted
Close appraisal result；
The output module, for exporting the first appraisal result, the first fusion appraisal result or the second fusion scoring knot
Fruit.
Preferably, the system also includes:
Setup module, for presetting the first system, second system and third system；Or
Selecting module, for the first system, second system and third system described in real-time selection.
Preferably, the setup module, specifically for the recognition confidence and evaluation result closed according to dependence test collection,
It selects the system of best performance as the first system, and selects the system complementary with the first system as second system.
Preferably, the selecting module is specifically used for according to system running environment or voice data feature, real-time selection the
One system, and select the system complementary with the first system as second system.
Preferably, the system also includes:
Condition determining module, for determining the first condition and second condition according to different application scenarios and demand.
Method and system for evaluating spoken language provided in an embodiment of the present invention adds on the basis of multisystem merges oral evaluation
Enter appraisal result arbitration functions, in the case where appraisal result is unsatisfactory for requirement, other evaluating systems is further selected to carry out again
Secondary scoring, and obtained a variety of appraisal results are merged, obtain final appraisal result.Therefore, guaranteeing evaluation and test performance
On the basis of, greatly improve evaluation and test efficiency.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only one recorded in the present invention
A little embodiments are also possible to obtain other drawings based on these drawings for those of ordinary skill in the art.
Fig. 1 is the flow chart of oral evaluation method of the embodiment of the present invention；
Fig. 2 is a kind of structural schematic diagram of oral evaluation system of the embodiment of the present invention.
Specific embodiment
The scheme of embodiment in order to enable those skilled in the art to better understand the present invention with reference to the accompanying drawing and is implemented
Mode is described in further detail the embodiment of the present invention.
For the lower problem of the fusion of multisystem in the prior art oral evaluation system evaluation efficiency, the embodiment of the present invention is mentioned
For a kind of method and system for evaluating spoken language, scores first with the first system voice data to be evaluated, obtain first
Appraisal result；Then judge whether the first appraisal result meets first condition, if it is, output first appraisal result,
Otherwise, it is scored using second system the voice data, obtains the second appraisal result；Subsequently determine whether the second appraisal result
Whether meet second condition, if it is, merging to first appraisal result and second appraisal result, obtains
One fusion appraisal result is simultaneously exported as final appraisal result, otherwise, is scored using third system the voice data,
Obtain third appraisal result；Finally first appraisal result, the second appraisal result and third appraisal result are merged, obtained
It exports to the second fusion appraisal result and as final appraisal result.
As shown in Figure 1, being the flow chart of oral evaluation method of the embodiment of the present invention, comprising the following steps:
Step 101, voice data to be evaluated is received.
Step 102, it is scored using the first system the voice data, obtains the first appraisal result.
Existing multisystem fusion oral evaluation system merges all single system appraisal results, therefore, to monosystem
The sequencing of system operation does not have particular requirement.This evaluating method is from the angle for improving system operations efficiency, in order to the greatest extent may be used
The evaluation and test sequence of the fast generation evaluation result of energy, each single system is quite important.The first system should be able to be solved accurately greatly
Partial evaluation and test problem.
Specifically, include following two for the selection method of the first system:
1) it presets, i.e., just sets the first system before system operation, no longer change in system operation.For pre-
The multiple evaluating systems being first arranged, can choose wherein any one evaluating system, can also be according in phase as the first system
Recognition confidence and evaluation result that test set closes are closed, selects the system with optimal performance or most robust as the first system
System.
2) real-time selection, system can according to current operating environment, or the characteristics of according to voice data to be evaluated etc.,
Real-time selection has the system of optimal representation as the first system.Such as: DNN(Deep Neural Network, deep layer nerve
Network) there is stronger expression ability for training data, DNN identifying system obtained from low signal-to-noise ratio training data, which is added, one
Fixed anti-noise ability can be real-time if the running environment of current system is relatively poor or data SNR to be evaluated is relatively low
Select the system identified based on DNN as the first system, otherwise selection is based on BN (Bottle-Neck) system identified or base
In GMM-HMM(Gaussian Mixture Model-Hidden Markov Model, gauss hybrid models-Hidden Markov
Model) identification system as the first system.
It should be noted that, institute different with two methods of the foundation of real-time selection selection the first system due to presetting
It is also different with applicable scene.It is real for the application scenarios of known speech evaluating data portion characteristic, system current operating situation
When select the first system method, can guarantee evaluate and test effect on the basis of, quickly obtain final evaluation result；For
Have the application scenarios of the evaluation result on dependence test collection, preset the first system (such as based on Bottle Neck identification
System) method have more advantage.
Step 103, judge whether the first appraisal result meets first condition.
The first condition can be determined according to different application scenarios and demand, be commented for example, can be described first
Result is divided to be higher than setting score value；Either the recognition confidence of the first system is higher than setting thresholding.
By judging whether the first appraisal result meets first condition, it is possible to prevente effectively from high score data are commented low ask
Topic, and then improve evaluation and test precision.
In the present embodiment, high score data are commented to low risk in order to reduce, first condition can choose as the first scoring
As a result whether it is higher than 80 points (hundred-mark system)；In order to improve the efficiency of multisystem fusion, first condition can be simply selected to be the
Whether the recognition confidence of one system is higher than setting thresholding.
Further, if the first appraisal result meets first condition, 109 are thened follow the steps, exports first scoring
As a result；Otherwise, step 104 is executed.
Step 104, it is scored using second system the voice data, obtains the second appraisal result.
Different speech recognition systems is such as based on PLP(Perceptual Linear based on different acoustic features
Predictive, perceive linear prediction) feature acoustic model, or use different acoustic models, such as based on the nerve net of DNN
Network acoustic model decodes voice data even being searched for using different decoding processes such as Viterbi.
Since different speech recognition systems has different decoding advantages, often have centainly between recognition result
Complementarity, therefore second system should have corresponding supplementary function to the first system, to improve the accuracy of evaluation and test.
For the selection method of second system equally preset with two kinds of real-time selection, specifically refer to the first system
Selection method, and will not be described here in detail.
Step 105, judge whether second appraisal result meets second condition.
The second condition can equally be determined according to different application scenarios and demand, for example, can be described
The difference of one appraisal result and second appraisal result is less than setting difference etc..
By judging whether the second appraisal result meets second condition, individual voice evaluation and test can be reduced to a certain extent
System exception or the extremely caused score abnormal conditions of evaluating object, and then improve evaluation and test precision.
In the present embodiment, different in order to reduce the extremely caused score of individual voice evaluating system exception or evaluating object
Reason condition, the second condition can be set to first appraisal result and the difference of second appraisal result is less than setting
Difference (such as 4%).
It should be noted that in practical applications, can also be loaded according to different examination types and be suitble to this type accordingly
The speech evaluating system of examination is mentioned by being compared to evaluation result of the same type evaluating system to different evaluating objects
Before judge system operation situation, the extremely caused score abnormal conditions of removal system, to further increase the operation of system
Efficiency and evaluation and test precision.
Further, if the second appraisal result meets second condition, 106 are thened follow the steps；Otherwise, step 107 is executed.
Step 106, first appraisal result and the second appraisal result are merged, obtains the first fusion scoring knot
Then fruit executes step 109, output the first fusion appraisal result.
In the present embodiment, high score data are commented into low caused appraisal result abnormal conditions in order to be effectively reduced, can adopted
A variety of amalgamation modes are taken, for example, higher appraisal result in the first appraisal result and the second appraisal result is taken to merge as first
Appraisal result, naturally it is also possible to use other amalgamation modes, without limitation to this embodiment of the present invention.
In practical application, for having run complementary stronger the first system (such as Bottle Neck) and second system
The pre- evaluation and test data of (such as GMM-HMM), if the appraisal result of the first system and second system is not much different, (for example difference is not
More than operation third system 4%), is not then needed, directly first appraisal result and the second appraisal result are merged, obtained
To the first fusion appraisal result；And it is exported as final appraisal result.
Step 107, it is scored using third system the voice data, obtains third appraisal result.
The third system has certain complementarity (integrality, accuracy, stream to the first system and second system
Sharp degree etc.).
Since different speech evaluating systems uses different recognizer or acoustic model, often there is different knowledges
Not as a result, evaluation and test score is also not quite similar accordingly, there is also certain complementarity between appraisal result.
For third system alternatives equally preset with two kinds of real-time selection, specifically refer to the first system
Selection method, and will not be described here in detail.
Step 108, first appraisal result, the second appraisal result and third appraisal result are merged, obtains
Two fusion appraisal results.
High score data are commented into low caused appraisal result abnormal conditions in order to be effectively reduced, take the first appraisal result, second
Highest appraisal result in appraisal result and third appraisal result is as the second fusion appraisal result.
It should be noted that under different application scenarios, can choose different system appraisal results in practical application
Fusion method.For example, high score data to be commented to low risk in order to reduce for formal examination, the method for system score fusion is
Take the peak of the first appraisal result, the second appraisal result and third appraisal result.And for other application scenarios, such as mould
Quasi- examination, machine indirect labor scoring etc., for the comprehensive condition of conservative estimation individual, the method for system score fusion can be selected
Take the average value of the first appraisal result, the second appraisal result and third appraisal result as the second fusion appraisal result.
Step 109, appraisal result is exported.
Scoring is added on the basis of multisystem merges oral evaluation in oral evaluation method provided in an embodiment of the present invention
As a result arbitration functions further select other evaluating systems to be scored again in the case where appraisal result is unsatisfactory for requirement,
And obtained a variety of appraisal results are merged, obtain final appraisal result.It not only ensure that the accuracy of evaluation result, and
And greatly improve evaluation and test efficiency.
Correspondingly, the embodiment of the present invention also provides a kind of oral evaluation system, as shown in Fig. 2, being a kind of knot of the system
Structure schematic diagram.
In this embodiment, the system comprises receiving module 201, the first system module 202, judgment module 203,
Two system module 204, the first Fusion Module 205, third system module 206, the second Fusion Module 207 and output module
208.Wherein:
Receiving module 201, for receiving voice data to be evaluated.
The first system module 202 obtains the first appraisal result for scoring the voice data.
Judgment module 203, for judging whether first appraisal result meets first condition, if it is, will be described
First appraisal result sends output module 208 to, so that the output module 208 exports first appraisal result；Otherwise, lead to
Know that second system module 204 scores to the voice data.
Above-mentioned first condition can be determined according to different application scenarios and demand, be commented for example, can be described first
Result is divided to be higher than setting score value；Either the recognition confidence of the first system is higher than setting thresholding etc..
Judgment module 203 is by judging whether the first appraisal result meets first condition, it is possible to prevente effectively from by balloon score
According to commenting low problem, and then improve assessment precision.
In the present embodiment, high score data are commented to low risk in order to reduce, first condition can choose as the first scoring
As a result whether it is higher than 80 points (hundred-mark system)；In order to improve the efficiency of multisystem fusion, first condition can simply be selected as the
Whether the recognition confidence of one system module is higher than setting thresholding.
Further, if the first appraisal result meets first condition, judgment module 203 notifies output module 208 defeated
First appraisal result out；Otherwise, notice second system module 204 evaluates and tests the voice data.
Second system module 204 obtains the second appraisal result for scoring the voice data.
Different speech recognition systems is such as based on PLP(Perceptual Linear based on different acoustic features
Predictive, perceive linear prediction) feature acoustic model, or use different acoustic models, such as based on the nerve net of DNN
Network acoustic model decodes voice data even being searched for using different decoding processes such as Viterbi.
Further, judgment module 203, are also used to judge whether second appraisal result meets second condition, if
It is that the first Fusion Module 205 is then notified to merge first appraisal result and the second appraisal result；Otherwise, is notified
Three system modules 206 score to the voice data.
Equally, above-mentioned second condition can also be determined according to different application scenarios and demand, for example, can be described
The difference of first appraisal result and second appraisal result is less than setting difference etc..
First Fusion Module 205, for merge and will obtain to first appraisal result and the second appraisal result
First fusion appraisal result send output module 208 to so that the output module 208 export it is described first fusion scoring knot
Fruit.
First Fusion Module 205 to the specific amalgamation mode of the first appraisal result and the second appraisal result can there are many,
For example take in the first appraisal result and the second appraisal result higher appraisal result as the first fusion appraisal result, or weighting
It is average etc..In practical application, Bottle is such as based on for having run complementary stronger above-mentioned the first system module 202(
Neck identification system) and second system module 204(such as based on GMM-HMM identify system) pre- evaluation and test data, if
The appraisal result of the first system module 202 and second system module 204 is not much different (for example difference is no more than 4%), then no longer needs
Third system module 206 is wanted to score the voice data, the first Fusion Module 205 is directly by first appraisal result
It is merged with the second appraisal result, obtains the first fusion appraisal result；And output module is sent to as final appraisal result
208。
Third system module 206 obtains third appraisal result for scoring the voice data.
The third system module 206 has centainly mutual to the first system module 202 and second system module 204
Benefit property (integrality, accuracy, fluency etc.).When second appraisal result is unsatisfactory for second condition, third system module
Pre- evaluation and test data are evaluated and tested.
It should be noted that since different speech evaluating systems uses different recognizer or acoustic model, it is past
Toward having different recognition results, corresponding score of evaluating and testing also is not quite similar, and there is also certain complementarity between appraisal result.
Second Fusion Module 207, for being carried out to first appraisal result, the second appraisal result and third appraisal result
It merges and sends the obtain second fusion appraisal result to output module 208, so that second fusion of the output of output module 208 is commented
Divide result.
Equally, the second Fusion Module 207 can also be using a variety of amalgamation modes to the first appraisal result, the second appraisal result
It is merged with third appraisal result, for example, high score data are commented into low caused appraisal result abnormal conditions in order to be effectively reduced,
Second Fusion Module 207 takes the highest appraisal result conduct in the first appraisal result, the second appraisal result and third appraisal result
Second fusion appraisal result, or these three appraisal results are weighted and averaged.Certainly, under different application scenarios, the
Two Fusion Modules 207 can select different fusion methods.For example, for formal examination, in order to reduce high score data are commented it is low
Risk, the second Fusion Module 207 can take the peak of the first appraisal result, the second appraisal result and third appraisal result to make
For the second fusion appraisal result.And for other application scenarios, such as mock examination, machine indirect labor scoring etc., in order to
The comprehensive condition of conservative estimation individual, the second Fusion Module 207 can take the first appraisal result, the second appraisal result and third to comment
Divide the average value of result as the second fusion appraisal result.
Output module 208, for exporting the first appraisal result, the first fusion appraisal result or the second fusion scoring knot
Fruit.
It is previously noted that above-mentioned first condition and second condition can be determined according to different application scenarios and demand, phase
Ying Di in the evaluating system of the embodiment of the present invention, is also provided with condition determining module in order to facilitate systematic difference
(not shown), for determining the first condition and second condition according to different application scenarios and demand.In this way, in difference
Application environment under, corresponding first condition and second condition easily can be arranged by the condition determining module.
In addition, in practical applications, above-mentioned the first system module 202, second system module 204 and third system module
206 are loaded with different types of oral evaluation system respectively, for convenience, are referred to as the first system, the second system respectively
System and third system.And the first system, second system and third system can be according to application environment and characteristic voices to be evaluated
To determine.For this purpose, can also further comprise in the oral evaluation system of the embodiment of the present invention: setup module or selecting module
(not shown).Wherein:
The setup module, for presetting the first system, second system and third system, such as can basis
The recognition confidence and evaluation result that dependence test collection closes select the system of best performance as the first system, and select with
The system of the first system complementation is as second system.
The selecting module, for the first system, second system and third system described in real-time selection, such as can basis
System running environment or voice data feature, real-time selection the first system, and the system complementary with the first system is selected to make
For second system.
In addition, it is necessary to which explanation, in practical applications, the single evaluating system of multiple and different types can be preset to
In the oral evaluation system of the embodiment of the present invention, each system module is selected to need by above-mentioned setup module by user to be loaded
System.Certainly, according to the thought of the embodiment of the present invention, the appraisal result of more triangular webs can also be merged, is obtained
To more accurate appraisal result, without limitation to this embodiment of the present invention.
Scoring is added on the basis of multisystem merges oral evaluation in oral evaluation system provided in an embodiment of the present invention
As a result arbitration functions further select other evaluating systems to be scored again in the case where appraisal result is unsatisfactory for requirement,
And obtained a variety of appraisal results are merged, obtain final appraisal result.It not only ensure that the accuracy of evaluation result, and
And greatly improve evaluation and test efficiency.
The same or similar parts between the embodiments can be referred to each other in this specification, for system embodiment
Speech, since it is substantially similar to the method embodiment, so describing fairly simple, referring to the part of embodiment of the method in place of correlation
Explanation.System embodiment described above is only schematical, wherein the module as illustrated by the separation member
It may or may not be physically separated, the component shown as module may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
In the case where labour, it can understand and implement.
Various component embodiments of the invention can be implemented in hardware, or to run on one or more processors
Software module realize, or be implemented in a combination thereof.It will be understood by those of skill in the art that can be used in practice
Microprocessor or digital signal processor (DSP) come realize some in oral evaluation system according to an embodiment of the present invention or
The some or all functions of person's whole component.The present invention is also implemented as one for executing method as described herein
Point or whole device or device programs (for example, computer program and computer program product).
The embodiment of the present invention has been described in detail above, and specific embodiment used herein carries out the present invention
It illustrates, the above description of the embodiments is only used to help understand the method and apparatus of the present invention；Meanwhile for the one of this field
As technical staff, according to the thought of the present invention, there will be changes in the specific implementation manner and application range, to sum up institute
It states, the contents of this specification are not to be construed as limiting the invention.
Claims (12)
1. a kind of oral evaluation method characterized by comprising
Receive voice data to be evaluated；
It is scored using the first system the voice data, obtains the first appraisal result；
If first appraisal result meets first condition, first appraisal result is exported；
Otherwise, it is scored using second system the voice data, obtains the second appraisal result；Wherein, second system pair
The first system has complementarity；
If second appraisal result meets second condition, to first appraisal result and second appraisal result into
Row fusion, obtains the first fusion appraisal result, then exports the first fusion appraisal result；
Otherwise, it is scored using third system the voice data, obtains third appraisal result；Wherein, third system pair
The first system and second system have complementarity；
First appraisal result, the second appraisal result and third appraisal result are merged, the second fusion scoring knot is obtained
Then fruit exports the second fusion appraisal result.
2. the method according to claim 1, wherein the method also includes:
Preset the first system, second system and third system；Or
The first system, second system described in real-time selection and third system.
3. according to the method described in claim 2, it is characterized in that, described preset the first system, second system and third
System includes:
The recognition confidence and evaluation result closed according to dependence test collection, selects the system of best performance as the first system；
Select the system complementary with the first system as second system.
4. according to the method described in claim 2, it is characterized in that, the first system described in the real-time selection, second system and
Third system includes:
According to system running environment or voice data feature, real-time selection the first system；
Select the system complementary with the first system as second system.
5. method according to any one of claims 1 to 4, which is characterized in that the method also includes:
According to different application scenarios and demand, the first condition and second condition are determined.
6. according to the method described in claim 5, it is characterized in that, the first condition be first appraisal result be higher than set
Determine score value；Or the first condition is the recognition confidence of the first system higher than setting thresholding.
7. according to the method described in claim 5, it is characterized in that, the second condition be first appraisal result with it is described
The difference of second appraisal result is less than setting difference.
8. a kind of oral evaluation system characterized by comprising
Receiving module, for receiving voice data to be evaluated；
The first system module obtains the first appraisal result for scoring the voice data；
Judgment module, for judging whether first appraisal result meets first condition, if it is, described first is scored
As a result output module is sent to, so that the output module exports first appraisal result；Otherwise, second system module is notified
It scores the voice data；
The second system module obtains the second appraisal result for scoring the voice data；Wherein, the second system
System has complementarity to the first system；
The judgment module, is also used to judge whether second appraisal result meets second condition, if it is, notifying first
Fusion Module merges first appraisal result and the second appraisal result；Otherwise, notice third system module is to described
Voice data scores；Wherein, third system has complementarity to the first system and second；
First Fusion Module, for merge and melt obtain first to first appraisal result and the second appraisal result
It closes appraisal result and sends output module to, so that output module output the first fusion appraisal result；
The third system module obtains third appraisal result for scoring the voice data；
Second Fusion Module, for being merged simultaneously to first appraisal result, the second appraisal result and third appraisal result
The obtain second fusion appraisal result is sent to the output module, so that output module output second fusion is commented
Divide result；
The output module, for exporting the first appraisal result, the first fusion appraisal result or the second fusion appraisal result.
9. system according to claim 8, which is characterized in that the system also includes:
Setup module, for presetting the first system, second system and third system；Or
Selecting module, for the first system, second system and third system described in real-time selection.
10. system according to claim 9 characterized by comprising
The setup module selects performance most specifically for the recognition confidence and evaluation result closed according to dependence test collection
Excellent system selects the system complementary with the first system as second system as the first system.
11. system according to claim 9 characterized by comprising
The selecting module is specifically used for according to system running environment or voice data feature, real-time selection the first system, and selects
The system complementary with the first system is selected as second system.
12. system according to any one of claims 8 to 11, which is characterized in that the system also includes:
Condition determining module, for determining the first condition and second condition according to different application scenarios and demand.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410139305.0A CN104978971B (en) | 2014-04-08 | 2014-04-08 | A kind of method and system for evaluating spoken language |
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| CN201410139305.0A CN104978971B (en) | 2014-04-08 | 2014-04-08 | A kind of method and system for evaluating spoken language |
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| Publication Number | Publication Date |
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| CN104978971A CN104978971A (en) | 2015-10-14 |
| CN104978971B true CN104978971B (en) | 2019-04-05 |
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| CN105741831B (en) * | 2016-01-27 | 2019-07-16 | 广东外语外贸大学 | A kind of oral evaluation method and system based on syntactic analysis |
| CN109426553A (en) | 2017-08-21 | 2019-03-05 | 上海寒武纪信息科技有限公司 | Task cutting device and method, Task Processing Unit and method, multi-core processor |
| CN110413551B (en) | 2018-04-28 | 2021-12-10 | 上海寒武纪信息科技有限公司 | Information processing apparatus, method and device |
| WO2019001418A1 (en) | 2017-06-26 | 2019-01-03 | 上海寒武纪信息科技有限公司 | Data sharing system and data sharing method therefor |
| CN109214616B (en) * | 2017-06-29 | 2023-04-07 | 上海寒武纪信息科技有限公司 | Information processing device, system and method |
| CN109273023B (en) * | 2018-09-20 | 2022-05-17 | 科大讯飞股份有限公司 | Data evaluation method, device and equipment and readable storage medium |
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| CN111128238B (en) * | 2019-12-31 | 2022-06-24 | 云知声智能科技股份有限公司 | Mandarin assessment method and device |
| CN114329040B (en) * | 2021-10-28 | 2024-02-20 | 腾讯科技（深圳）有限公司 | Audio data processing method, device, storage medium, equipment and program product |
| CN115798519B (en) * | 2023-02-10 | 2023-05-05 | 山东山大鸥玛软件股份有限公司 | English multi-question type spoken language pronunciation assessment method and system |
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