CN103686833A - Mobile network voice quality estimating method and device - Google Patents
Mobile network voice quality estimating method and device Download PDFInfo
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Abstract
The invention discloses a mobile network voice quality estimating method and device and relates to the technical field of mobile communication. The problem that a voice estimation result which reflects true feelings of a random user all over the network can be not obtained with low cost in the prior art is solved. The method includes the following steps that data which are relevant to a voice service and recorded in all devices in the mobile network are obtained; a property set is set up according to all properties in the data and divided into a property sub-set of an access process, a property sub-set of a maintaining process and a property sub-set of a complete process, and values of all the properties in the property set are zero; a data set relevant to a designated incident of a designated user in the data is obtained and corresponding properties in the property set are valuated according to property values of all the properties in the data set and a single-user single-event set is formed; all the sub-sets are calculated respectively and a quality estimation value of the access process, a quality estimation value of the maintaining process and a quality estimation value of the complete process are obtained; according to all the quality estimation values, a mobile network voice quality estimation result is obtained.
Description
Technical field
The present invention relates to mobile communication technology, relate in particular to mobile network's speech quality assessment method and device.
Background technology
For mobile communications network, speech business is its most crucial, most basic class of business providing, and its quality evaluation is also the major criterion of weighing network performance naturally.Existing mobile network's speech quality assessment method comprises: equipment performance statistical method, road measuring method etc.
Wherein, equipment performance statistical method is to be responsible for by mobile communications network network management system, mainly obtain the performance data of each device interior in network and carry out statistical analysis, as obtain certain equipment (radio network controller, base station controller, base station etc.) rising in a specific measurement period and exhale number of attempt, rise and exhale number of success, switching times, number of dropped calls etc. and these data are carried out to statistical analysis, utilize analysis result can macroscopically reflect the quality of the speech business of this equipment reception.But in the method, because equipment can only provide statistics for the fault of the dominant problem of signaling process or inter-process, covered the recessive failure information of some on existing network, can not reflect user's sense of reality, as connected, connect speed, whether call drop, voice quality quality etc.
Road measuring method can allow assessment result reflect better user's sense of reality, this method is to adopt special-purpose voice testing equipment, carry out continual speech business testing corresponding test scene (as high ferro, super expressway) is inner, follow the tracks of standard agreement message and the user's face content that captures the corresponding interface simultaneously, and on the basis of these information, voice quality is assessed.But the method is due to the restriction of test specification, testing tool, testing time, mode of operation, and the information of obtaining is all a certain amount of sampled value, has certain limitation, can not reflect the real voice quality of the whole network completely; Meanwhile, the method needs special messenger, special train test, and cost is also higher.
Summary of the invention
Embodiments of the invention provide a kind of mobile network's speech quality assessment method and device, have solved prior art and cannot obtain with lower cost the problem of the voice assessment result of any user's sense of reality of reflection the whole network.
For achieving the above object, embodiments of the invention adopt following technical scheme:
Mobile network's speech quality assessment method, comprising: (1) obtains the data relevant to speech business that record in each equipment of mobile network, and each packet is containing a plurality of attributes, and each attribute has property value; (2) according to attributes all in described data, set up community set, and described community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, in described community set, the value of each attribute is 0; (3) obtain data set relevant to the allocate event of designated user in described data, and according to the property value of described data centralization all properties, the respective attributes in described community set is carried out to assignment, form alone family single event property set; (4) according to the first assessment algorithm of the property value of each attribute in access procedure attribute set and appointment, calculate and obtain access procedure quality assessment value A; (5) according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment, calculate and obtain keep-process quality assessment value B; (6) according to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value C; (7) according to described access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, calculate, obtain mobile network's speech quality evaluation result D of the allocate event of described designated user.
Alternatively, described access procedure attribute set comprises: signaling process failure attribute a1, signaling failure cause attribute a2, customer complaint attribute a3 and corresponding property value; When signaling process failure, a1=1, when signaling process success, a1=0; When signaling failure cause is user's reason, a2=0, when signaling failure cause is network reason, a2=1; When there is no customer complaint, a3=0, when there is customer complaint, a3=1;
Described the first assessment algorithm according to the property value of each attribute in access procedure attribute set and appointment calculates acquisition access procedure quality assessment value A and comprises:
Access procedure quality assessment value A=5 is set;
If a3=1, A=0;
Work as a3=0, if a1=1 and a2=0, A=A-1, if a1=1 and a2=1, A=A-3;
If A<0, A=0.
Alternatively, described keep-process attribute set comprises: signaling process failure attribute b1, signaling failure cause attribute b2, GPEH flow process abnormal attribute b3, the abnormal scene properties b4 of GPEH, customer complaint attribute b5 and corresponding property value; When signaling process failure, b1=1, when signaling process success, b1=0; When signaling failure cause is user's reason, b2=0, when signaling failure cause is network reason, b2=1; When there is no customer complaint, b5=0, when there is customer complaint, b5=1; When GPEH flow process is normal, b3=0, when GPEH flow process is abnormal, b3=1;
Described the second assessment algorithm according to the property value of each attribute in keep-process attribute set and appointment calculates acquisition keep-process quality assessment value B and comprises:
Keep-process quality assessment value B=5 is set;
If b5=1, B=0;
When b5=0, if b1=1 and b2=0, B=B-1, if b1=1 and b2=1, B=B-3;
If the first penalties is set according to the property value of b4 during b3=1, from B, deduct described the first penalties;
If B<0, B=0.
Alternatively, described complete procedure attribute set comprises: signaling process failure attribute c1, signaling failure cause attribute c2, GPEH flow process abnormal attribute c3, the abnormal scene properties c4 of GPEH, measurement report attribute c5, customer complaint attribute c6 and corresponding property value; When signaling process failure, c1=1, when signaling process success, c1=0; When signaling failure cause is user's reason, c2=0, when signaling failure cause is network reason, c2=1; When there is no customer complaint, c6=0, when there is customer complaint, c6=1; When GPEH flow process is normal, c3=0, when GPEH flow process is abnormal, c3=1;
Described the 3rd assessment algorithm according to the property value of each attribute in complete procedure attribute set and appointment calculates acquisition complete procedure quality assessment value C and comprises:
Keep-process quality assessment value C=5 is set;
If c6=1, C=0;
When c6=0, if c1=1 and c2=0, C=C-1, if c1=1 and c2=1, C=C-3;
If the second penalties is set according to the property value of c4 during c3=1, from C, deduct described the second penalties;
According to the property value of c5, the 3rd penalties is set, from C, deducts described the 3rd penalties;
If C<0, C=0.
Preferably, describedly according to described access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, the mobile network's speech quality evaluation result D that obtains the allocate event of described designated user comprises:
Be 0 one of in A, B, C, D=0; Otherwise,
Alternatively, described mobile network's speech quality assessment method also comprises:
The first access failure threshold value N0, the second access failure threshold value N1, the 3rd access failure threshold value N2 and the 4th access failure threshold value N3 are set, N0 < N1 < N2 < N3; The first number of dropped calls threshold value M0, the second number of dropped calls threshold value M1, the 3rd number of dropped calls threshold value M2 and the 4th number of dropped calls threshold value M3 are set, M0 < M1 < M2 < M3; The first frequency threshold value P0 of poor quality, the second frequency threshold value P1 of poor quality, the 3rd frequency threshold value P2 of poor quality and the 4th frequency threshold value P3 of poor quality are set, P0 < P1 < P2 < P3;
As A < N0, access procedure quality is excellent; As N0 < A < N1, access procedure quality is good; As N1 < A < N2, during access procedure quality is; As N2 < A < N3, access procedure quality is for poor;
As B < M0, keep-process quality is excellent; As M0 < B < M1, keep-process quality is good; As M1 < B < M2, during keep-process quality is; As M2 < B < M3, keep-process quality is for poor;
As C < P0, complete procedure quality is excellent; As P0 < C < P1, complete procedure quality is good; As P1 < C < P2, during complete procedure quality is; As P2 < C < P3, complete procedure quality is for poor.
Further, describedly according to described access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, the mobile network's speech quality evaluation result D that obtains the allocate event of described designated user comprises:
When access procedure quality, keep-process quality and complete procedure quality are excellent, mobile network's speech quality evaluation result D is excellent; When access procedure quality, keep-process quality and complete procedure quality are good, mobile network's speech quality evaluation result D is good; In access procedure quality, keep-process quality and complete procedure quality are, during mobile network's speech quality evaluation result D is; When access procedure quality, keep-process quality and complete procedure quality are poor, mobile network's speech quality evaluation result D is for poor; When access procedure quality, keep-process quality and complete procedure quality are inconsistent, mobile network's speech quality evaluation result D gets minimum in three.
Preferably, described mobile network's speech quality assessment method also comprises:
(8) fixed time section, determines that the event in described fixed time section of described designated user is described allocate event;
(9) respectively allocate event described in each is carried out to step (3) to the processing of step (7), obtain mobile network's speech quality evaluation result of the allocate event of described designated user;
(10) mobile network's speech quality evaluation result described in each is calculated according to the 5th assessment algorithm, obtained alone family comprehensive evaluation result.
Further, described mobile network's speech quality assessment method also comprises:
(11) specify other user who is associated with described designated user, repeating step (8) is to step (10), obtains the described alone family comprehensive evaluation result of other user described in each;
(12) all described alone families comprehensive evaluation result is calculated according to the 6th assessment algorithm, obtain customer group comprehensive evaluation result.
Mobile network's speech quality evaluation device, comprising:
Data acquisition module, the data relevant to speech business that record for obtaining each equipment of mobile network, each packet is containing a plurality of attributes, and each attribute has property value;
Community set is set up module, for setting up community set according to all attributes of described data, and described community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, in described community set, the value of each attribute is 0;
Attribute assignment module, for obtaining the data set that described data are relevant to the allocate event of designated user, and carries out assignment according to the property value of described data centralization all properties to the respective attributes in described community set, forms alone family single event property set;
Process assessment module, obtains access procedure quality assessment value for calculating according to the first assessment algorithm of the property value of each attribute of access procedure attribute set and appointment; And calculate and obtain keep-process quality assessment value according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment; According to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value again;
Event evaluation module, for calculating according to described access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, obtain mobile network's speech quality evaluation result of the allocate event of described designated user.
Mobile network's speech quality assessment method and device that the embodiment of the present invention provides, customer-centric, obtain the existing Various types of data relevant to voice of mobile network, according to these data, set up by access procedure attribute set again, the community set that keep-process attribute set and complete procedure attribute set form, and be that each attribute assignment in community set is to form the alone family single event property set of user class, relend and help different algorithms to calculate each attribute set, obtain respectively the quality assessment value of each process, thereby obtain each client at audio access, retentivity, the impression of integrality aspect, finally according to each quality assessment value, obtain the speech quality evaluation result of the unique user of the perception of being more close to the users, the method is owing to not needing special equipment, and realize evaluation process according to existing data, can reduce assessed cost, and the data of the data of using for recording in distinct device running in mobile network, data volume is large, the information of reflection is comprehensive, can improve the accuracy of assessment.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, below the accompanying drawing of required use during embodiment is described is briefly described.
The flow chart of mobile network's speech quality assessment method that Fig. 1 provides for the embodiment of the present invention;
Multi-user's flow chart of speech quality assessment method of event of repeatedly conversing in a period of time that Fig. 2 provides for the embodiment of the present invention;
The block diagram of mobile network's speech quality evaluation device that Fig. 3 provides for the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described.
The embodiment of the present invention provides a kind of mobile network's speech quality assessment method, and as shown in Figure 1, the method comprises the steps.
101, obtain the data relevant to speech business that record in each equipment of mobile network, each packet is containing a plurality of attributes, and each attribute has property value.
Particularly, these data are from equipment different in mobile network, as signaling acquisition system, wireless device webmaster, customer complaint platform etc., these data are all relevant to speech business, and every kind of data all have certain data structure, that is to say, every kind of data all include a plurality of attributes, such as user ID, Time To Event etc., and every kind of attribute all has corresponding property value.The user ID that the property value comprising as a kind of data is ID1, property value is the Time To Event in 7: 04: 12 morning of on November 12nd, 2006, in data, also can comprise other attribute, signaling process failure attribute for example, customer complaint attribute etc., wherein, user ID can be IMSI(International Mobile Subscriber Identification Number, international mobile subscriber identity), MSISDN(Mobile Subscriber International ISDN/PSTN number, mobile station identity number) or TMSI(Temporary Mobile Subscriber Identity, interim identification code), or other energy unique identification user's attribute.
102, according to attributes all in data, set up community set, and community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, in community set, the value of each attribute is 0.
Conventionally, in voice call process, relate to the access procedure making a call, connected later call keep-process.Whether smoothly each process is carried out has directly affected the impression of user to speech business, such as when the calling defendant, due to network failure, call is not also connected and is just gone offline, or after connecting, call does not finish just to go offline, if these situations of being close to the users impression associate with mobile network's speech quality evaluation, the result that just can make the to assess impression of being more close to the users.
Therefore, the embodiment of the present invention is divided the community set of setting up according to all properties in data, has formed access procedure attribute set, keep-process attribute set and complete procedure attribute set.Make the attribute relevant to access procedure form access procedure attribute set, the attribute relevant to keep-process forms keep-process attribute set, and the attribute relevant to the complete procedure consisting of access procedure and keep-process forms complete procedure attribute set.And each attribute in community set has initial value 0.
103, obtain data set relevant to the allocate event of designated user in data, and according to the property value of data centralization all properties, the respective attributes in community set is carried out to assignment, form alone family single event property set.
Particularly, the event described in the present invention is voice call event, comprises caller call and incoming call.
Judging whether each data are relevant to designated user need to be by this attribute of user ID in data, designated user refers to the user who has specified user ID, in each data, the property value of user ID is identical with designated user sign, and these data are relevant to designated user.
In the data relevant to designated user, judge each data whether with allocate event relevant need to be by data in this attribute of time of origin, also different according to the different decision method of data type.Wherein, allocate event refers to the event of having specified time of origin.
That in each equipment of mobile network, records comprises with speech business related data the active data producing in equipment running process, as signaling data, and is the passive data that typing produces by people, as customer complaint data.In these two kinds of data, all comprise time of origin attribute, the time of origin of signaling data is produced by device hardware, can be as accurate as a second level, as the signaling data of record in 7: 04: 12 morning of on November 12nd, 2006, the time of origin of customer complaint data is provided by the client who complains, and conventionally can only be accurate to the morning or afternoon in the middle of certain day.
Therefore in the data relevant to designated user, judge that whether each active data is relevant to allocate event, only need the property value of time of origin all identical with appointment time of origin, these active data are relevant to the allocate event of designated user.For example, in the first active data, comprising user ID, the property value that property value is ID1 is the time of origin in 7: 04: 12 morning of on November 12nd, 2006 and the access signaling procedure failure attribute that property value is 0, comprises user ID, property value that property value is ID1 and be the time of origin in 7: 04: 12 morning of on November 12nd, 2006 and maintenance signaling procedure failure attribute that property value is 1 in the second active data.When the user ID of designated user is ID1, the time of origin of allocate event is 7: 04: 12 morning of on November 12nd, 2006, and these two data belong to the data relevant to the allocate event of designated user.
In the data relevant to designated user, judge that whether passive data are relevant to allocate event, because the accuracy of this data time of origin property value is different from the fixed time, can not determine that both are relevant by time of origin property value is identical, a kind of time match rule can only be set, in legal situation, determine that both are relevant.For example passive data are customer complaint data, first the time of origin property value of these data is mapped as and is accurate to a second time of origin property value for level, as worked as time of origin, it it is the morning on November 12nd, 2006, the property value of time of origin is designated as 9: 00: 00 morning of on November 12nd, 2006, when time of origin be afternoon on November 12nd, 2006 the property value of time of origin be designated as 4: 00: 00 afternoon of on November 12nd, 2006, certainly the rule of mapping is not limited to this, can arrange according to actual needs; Stipulated time matched rule is again: after mapping, time of origin property value is the data relevant with the allocate event of designated user to the immediate passive data of appointment time of origin.For example, in the data relevant to designated user, after the mapping of certain customer complaint data, time of origin property value is 9: 00: 00 morning of on November 12nd, 2006, this time is the most approaching with appointment time of origin (7: 04: 12 morning of on November 12nd, 2006), and certain customer complaint data is the data relevant to the allocate event of designated user.
The relevant common composition data collection of data of the allocate event to designated user of determining according to said method.
Next need, according to the property value of data centralization all properties, the respective attributes in community set is carried out to assignment.For example the property value of data centralization access signaling flow process failure attribute is 0, keeping the property value of flow process failure attribute is 1, in community set, the property value assignment of the failure of the signaling process in access procedure attribute set attribute is 0, and the property value assignment of the signaling process failure attribute in keep-process attribute set is 1.
In some cases, voice call event is just failure in access procedure, situation about cannot connect, this is to there will not be follow-up keep-process and complete procedure, therefore can the generation data relevant to keep-process and complete procedure, make data centralization not have the attribute relevant to keep-process and complete procedure.At this moment, in community set, in keep-process attribute set and complete procedure attribute set, the property value of each attribute can, by assignment, still not remain on the initial value 0 arranging in step 102.
104, according to the first assessment algorithm of the property value of each attribute in access procedure attribute set and appointment, calculate and obtain access procedure quality assessment value A.
Particularly, this step and 105 steps below and 106 steps, can to the property value in each subset, calculate according to the assessment algorithm of ready-portioned attribute set and their correspondences, form respectively the quantitative evaluation value of access procedure, keep-process, complete procedure.This assessed value has directly embodied the impression to speech quality of user in each process of a voice call event.
Certainly, assessment algorithm can adopt the average or Weighted Average Algorithm of each property value, also can adopt other known to those skilled in the art can obtain the algorithm of reaction speech quality assessed value.
105, according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment, calculate and obtain keep-process quality assessment value B.
106, according to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value C.
107, according to access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, calculate, obtain mobile network's speech quality evaluation result D of the allocate event of designated user.
Finally, according to the assessed value and the corresponding assessment algorithm that calculate each process obtaining, obtain the voice quality comprehensive assessment result of the allocate event of this designated user.
Certainly, assessment algorithm can adopt the average or Weighted Average Algorithm of each property value, also can adopt other known to those skilled in the art can obtain the algorithm of reaction speech quality assessment result.
Mobile network's speech quality assessment method that the embodiment of the present invention provides, customer-centric, obtain the existing Various types of data relevant to voice of mobile network, according to these data, set up by access procedure attribute set again, the community set that keep-process attribute set and complete procedure attribute set form, and be that each attribute assignment in community set is to form the alone family single event property set of user class, relend and help different algorithms to calculate each attribute set, obtain respectively the quality assessment value of each process, thereby obtain each client at audio access, retentivity, the impression of integrality aspect, finally according to each quality assessment value, obtain the speech quality evaluation result of the unique user of the perception of being more close to the users, the method is owing to not needing special equipment, and realize evaluation process according to existing data, can reduce assessed cost, and the data of the data of using for recording in distinct device running in mobile network, data volume is large, the information of reflection is comprehensive, can improve the accuracy of assessment.
The preferred embodiment of introducing respectively the first assessment algorithm to the four assessment algorithms below, these algorithms coordinate selected property value, the sense of reality that the quality assessment value that can make to draw is more close to the users.
As shown in table 1, access procedure attribute set comprises: signaling process failure attribute a1, signaling failure cause attribute a2, customer complaint attribute a3 and corresponding property value; When signaling process failure, a1=1, when signaling process success, a1=0; When signaling failure cause is user's reason, a2=0, when signaling failure cause is network reason, a2=1; When there is no customer complaint, a3=0, when there is customer complaint, a3=1.
Table 1
According to the first assessment algorithm of the property value of each attribute in access procedure attribute set and appointment, calculating acquisition access procedure quality assessment value A specifically comprises: access procedure quality assessment value A=5 is set; If a3=1, while there is customer complaint, A=0; When a3=0, while there is no customer complaint, if a1=1 and a2=0, i.e. signaling process failure and be user's reason, A=A-1, if a1=1 and a2=1, signaling process is unsuccessfully and be network reason, A=A-3; Finally, if A<0, A=0.By the method, can calculate access procedure quality assessment value A.
As shown in table 2, keep-process attribute set comprises: signaling process failure attribute b1, signaling failure cause attribute b2, GPEH flow process abnormal attribute b3, the abnormal scene properties b4 of GPEH, customer complaint attribute b5 and corresponding property value; When signaling process failure, b1=1, when signaling process success, b1=0; When signaling failure cause is user's reason, b2=0, when signaling failure cause is network reason, b2=1; When there is no customer complaint, b5=0, when there is customer complaint, b5=1; When GPEH flow process is normal, b3=0, when GPEH flow process is abnormal, b3=1.Wherein, GPEH(General performance event handling, conventional performance event handling) be the radio network controller (RNC of Ericsson, Radio Network Controller) the call record data of device interior, also there are similar call record data in other communication equipment producers, as Nuo Xi be Traffica, in emerging be CDT, Huawei be CHR etc.This step has been extracted these data of GPEH as attribute, also can extract as required other producer's device interior data as attribute.
Table 2
According to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment, calculate and obtain keep-process quality assessment value B, specifically comprise: keep-process quality assessment value B=5 is set; If, there is customer complaint, B=0 in b5=1; When b5=0, while there is not customer complaint, if b1=1 and b2=0, and signaling process failure and be user's reason, B=B-1, if b1=1 and b2=1, signaling process is unsuccessfully and be network reason, B=B-3; If during b3=1, when GPEH flow process is abnormal, according to the property value of b4, the first penalties is set, from B, deduct the first penalties; Finally, if B<0, B=0.By the method, can obtain keep-process quality assessment value B.Wherein, can set according to the correlation degree between the voice quality of the abnormal scene of GPEH flow process and user impression the size of the first penalties, as 1,1.5 or 2 etc.
As shown in table 3, complete procedure attribute set comprises: signaling process failure attribute c1, signaling failure cause attribute c2, GPEH flow process abnormal attribute c3, the abnormal scene properties c4 of GPEH, measurement report attribute c5, customer complaint attribute c6 and corresponding property value; When signaling process failure, c1=1, when signaling process success, c1=0; When signaling failure cause is user's reason, c2=0, when signaling failure cause is network reason, c2=1; When there is no customer complaint, c6=0, when there is customer complaint, c6=1; When GPEH flow process is normal, c3=0, when GPEH flow process is abnormal, c3=1; The value of measurement report attribute c5 is that radio environment information in last 4 measurement reports (MR) is asked for after average, again according to the standard of wireless environment quality is judged and obtained average, for 3G network, c5 is { RSCP, Ec/Io}, when with { RSCP>-95dbm, when Ec/Io>-12db} is the high-quality standard of wireless environment intensity, if while meeting the requiring of " RSCP>-95dbm " and " Ec/Io>-12db " in the time of c5, c5=1, otherwise c5=0.
Table 3
According to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value C, specifically comprise: keep-process quality assessment value C=5 is set; If, there is customer complaint, C=0 in c6=1; When c6=0, while there is not customer complaint, if c1=1 and c2=0, i.e. signaling process failure and be user's reason, C=C-1, if c1=1 and c2=1, signaling process is unsuccessfully and be network reason, C=C-3; If during c3=1, when GPEH flow process is abnormal, according to the property value of c4, the second penalties is set, from C, deduct described the second penalties; According to the property value of c5, the 3rd penalties is set again, from C, deducts described the 3rd penalties; Finally, if C<0, C=0.By the method, can obtain complete procedure quality assessment value C.Wherein, can set according to the correlation degree between the voice quality of the abnormal scene of GPEH flow process and user impression the size of the second penalties, as 1,1.5 or 2 etc.Also can set according to the correlation degree between the voice quality of the value of c5 and user impression the size of the 3rd penalties, as 1,2 or 3 etc.
Finally, according to above-mentioned access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, obtain mobile network's speech quality evaluation result D of the allocate event of designated user, specifically comprise: be 0 one of in A, B, C, D=0; Otherwise,
and when A, B, C are not 0, after the mean value of calculating A, B, C also rounds downwards, as mobile network's speech quality evaluation result D.
Mobile network's speech quality evaluation result D that the method for above-mentioned calculating mean value obtains, for concrete numerical value, can be for mobile network's voice quality is carried out to quantitative assessment, we can also profit come mobile network's voice quality to assess qualitatively in the following method.
Qualitative evaluation method comprises: the first access failure threshold value N0, the second access failure threshold value N1, the 3rd access failure threshold value N2 and the 4th access failure threshold value N3 are set, N0 < N1 < N2 < N3; The first number of dropped calls threshold value M0, the second number of dropped calls threshold value M1, the 3rd number of dropped calls threshold value M2 and the 4th number of dropped calls threshold value M3 are set, M0 < M1 < M2 < M3; The first frequency threshold value P0 of poor quality, the second frequency threshold value P1 of poor quality, the 3rd frequency threshold value P2 of poor quality and the 4th frequency threshold value P3 of poor quality are set, P0 < P1 < P2 < P3.
Table 4 with reference to below, can carry out qualitative evaluation to the quality of access procedure, keep-process and complete procedure.
Table 4
As can be seen from Table 4: as A < N0, access procedure quality is excellent; As N0 < A < N1, access procedure quality is good; As N1 < A < N2, during access procedure quality is; As N2 < A < N3, access procedure quality is for poor; As B < M0, keep-process quality is excellent; As M0 < B < M1, keep-process quality is good; As M1 < B < M2, during keep-process quality is; As M2 < B < M3, keep-process quality is for poor; As C < P0, complete procedure quality is excellent; As P0 < C < P1, complete procedure quality is good; As P1 < C < P2, during complete procedure quality is; As P2 < C < P3, complete procedure quality is for poor.
The qualitative quality results obtaining with reference to table 4, according to access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, obtain mobile network's speech quality evaluation result D of the allocate event of designated user, specifically comprise: when access procedure quality, keep-process quality and complete procedure quality are excellent, mobile network's speech quality evaluation result D is excellent; When access procedure quality, keep-process quality and complete procedure quality are good, mobile network's speech quality evaluation result D is good; In access procedure quality, keep-process quality and complete procedure quality are, during mobile network's speech quality evaluation result D is; When access procedure quality, keep-process quality and complete procedure quality are poor, mobile network's speech quality evaluation result D is for poor; When access procedure quality assessment value A, keep-process quality assessment value B and complete procedure quality assessment value C are when inconsistent, mobile network's speech quality evaluation result D gets minimum in three.
In the not identical various situations of the quality assessment value at A, B, C, mobile network's speech quality evaluation result D gets minimum in three, and if A is that excellent, B is good, C when poor, D is for poor.
The method that above embodiment describes has only been carried out speech quality evaluation for the allocate event of designated user.The voice quality of the multiple events that the present invention can also occur designated user within a period of time is carried out comprehensive assessment, also can be further by a plurality of users the comprehensive assessment result within this period again carry out comprehensive assessment, thereby obtain the speech quality evaluation result of specific user/particular group/the whole network level.Concrete steps as shown in Figure 2.
201, fixed time section, determine designated user at the appointed time section in an event be allocate event.
202, respectively each allocate event is carried out to step 103 to the processing of step 107, obtain mobile network's speech quality evaluation result of the allocate event of designated user.
203, each mobile network's speech quality evaluation result is calculated according to the 5th assessment algorithm, obtained alone family comprehensive evaluation result.
204, other user who is associated of appointment and designated user, repeating step 201, to step 203, obtains each other user's alone family comprehensive evaluation result.
205, all alone families comprehensive evaluation result is calculated according to the 6th assessment algorithm, obtain customer group comprehensive evaluation result.
Wherein, the 5th assessment algorithm and the 6th assessment algorithm can adopt average algorithm or Weighted Average Algorithm.In a plurality of users of appointment, each user's grade is different, if any user be VIP client, have plenty of normal client, the 6th assessment algorithm just can adopt Weighted Average Algorithm, VIP client distributes higher weights, normal client is distributed lower weights.
The embodiment of the present invention also provides a kind of mobile network's speech quality evaluation device, as shown in Figure 3, this device comprises: data acquisition module 31, the data relevant to speech business that record for obtaining each equipment of mobile network, each packet is containing a plurality of attributes, and each attribute has property value; Community set is set up module 32, for setting up community set according to all attributes of data, and community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, and in community set, the value of each attribute is 0; Attribute assignment module 33, for obtaining the data set that data are relevant to the allocate event of designated user, and carries out assignment according to the property value of data centralization all properties to the respective attributes in community set, forms alone family single event property set; Process assessment module 34, obtains access procedure quality assessment value for calculating according to the first assessment algorithm of the property value of each attribute of access procedure attribute set and appointment; And calculate and obtain keep-process quality assessment value according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment; According to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value again; Event evaluation module 35, for calculating according to access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, obtains mobile network's speech quality evaluation result of the allocate event of designated user.
In this device, the performed method of each module have been described in detail in embodiment of the method, does not repeat them here.
Mobile network's speech quality evaluation device that the embodiment of the present invention provides, customer-centric, obtain the existing Various types of data relevant to voice of mobile network, according to these data, set up by access procedure attribute set again, the community set that keep-process attribute set and complete procedure attribute set form, and be that each attribute assignment in community set is to form the alone family single event property set of user class, relend and help different algorithms to calculate each attribute set, obtain respectively the quality assessment value of each process, thereby obtain each client at audio access, retentivity, the impression of integrality aspect, finally according to each quality assessment value, obtain the speech quality evaluation result of the unique user of the perception of being more close to the users, this device can be used the server in existing mobile network, do not need other special equipment, and realize evaluation process according to existing data, can reduce assessed cost, and the data of the data of using for recording in distinct device running in mobile network, data volume is large, the information of reflection is comprehensive, can improve the accuracy of assessment.
The above; be only the specific embodiment of the present invention, but protection scope of the present invention is not limited to this, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of described claim.
Claims (10)
1. mobile network's speech quality assessment method, is characterized in that, comprising: (1) obtains the data relevant to speech business that record in each equipment of mobile network, and each packet is containing a plurality of attributes, and each attribute has property value; (2) according to attributes all in described data, set up community set, and described community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, in described community set, the value of each attribute is 0; (3) obtain data set relevant to the allocate event of designated user in described data, and according to the property value of described data centralization all properties, the respective attributes in described community set is carried out to assignment, form alone family single event property set; (4) according to the first assessment algorithm of the property value of each attribute in access procedure attribute set and appointment, calculate and obtain access procedure quality assessment value A; (5) according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment, calculate and obtain keep-process quality assessment value B; (6) according to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value C; (7) according to described access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, calculate, obtain mobile network's speech quality evaluation result D of the allocate event of described designated user.
2. mobile network's speech quality assessment method according to claim 1, is characterized in that, described access procedure attribute set comprises: signaling process failure attribute a1, signaling failure cause attribute a2, customer complaint attribute a3 and corresponding property value; When signaling process failure, a1=1, when signaling process success, a1=0; When signaling failure cause is user's reason, a2=0, when signaling failure cause is network reason, a2=1; When there is no customer complaint, a3=0, when there is customer complaint, a3=1;
Described the first assessment algorithm according to the property value of each attribute in access procedure attribute set and appointment calculates acquisition access procedure quality assessment value A and comprises:
Access procedure quality assessment value A=5 is set;
If a3=1, A=0;
Work as a3=0, if a1=1 and a2=0, A=A-1, if a1=1 and a2=1, A=A-3;
If A<0, A=0.
3. mobile network's speech quality assessment method according to claim 1, it is characterized in that, described keep-process attribute set comprises: signaling process failure attribute b1, signaling failure cause attribute b2, GPEH flow process abnormal attribute b3, the abnormal scene properties b4 of GPEH, customer complaint attribute b5 and corresponding property value; When signaling process failure, b1=1, when signaling process success, b1=0; When signaling failure cause is user's reason, b2=0, when signaling failure cause is network reason, b2=1; When there is no customer complaint, b5=0, when there is customer complaint, b5=1; When GPEH flow process is normal, b3=0, when GPEH flow process is abnormal, b3=1;
Described the second assessment algorithm according to the property value of each attribute in keep-process attribute set and appointment calculates acquisition keep-process quality assessment value B and comprises:
Keep-process quality assessment value B=5 is set;
If b5=1, B=0;
When b5=0, if b1=1 and b2=0, B=B-1, if b1=1 and b2=1, B=B-3;
If the first penalties is set according to the property value of b4 during b3=1, from B, deduct described the first penalties;
If B<0, B=0.
4. mobile network's speech quality assessment method according to claim 1, it is characterized in that, described complete procedure attribute set comprises: signaling process failure attribute c1, signaling failure cause attribute c2, GPEH flow process abnormal attribute c3, the abnormal scene properties c4 of GPEH, measurement report attribute c5, customer complaint attribute c6 and corresponding property value; When signaling process failure, c1=1, when signaling process success, c1=0; When signaling failure cause is user's reason, c2=0, when signaling failure cause is network reason, c2=1; When there is no customer complaint, c6=0, when there is customer complaint, c6=1; When GPEH flow process is normal, c3=0, when GPEH flow process is abnormal, c3=1;
Described the 3rd assessment algorithm according to the property value of each attribute in complete procedure attribute set and appointment calculates acquisition complete procedure quality assessment value C and comprises:
Keep-process quality assessment value C=5 is set;
If c6=1, C=0;
When c6=0, if c1=1 and c2=0, C=C-1, if c1=1 and c2=1, C=C-3;
If the second penalties is set according to the property value of c4 during c3=1, from C, deduct described the second penalties;
According to the property value of c5, the 3rd penalties is set, from C, deducts described the 3rd penalties;
If C<0, C=0.
5. mobile network's speech quality assessment method according to claim 1, it is characterized in that, describedly according to described access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, the mobile network's speech quality evaluation result D that obtains the allocate event of described designated user comprises:
Be 0 one of in A, B, C, D=0; Otherwise,
6. according to the mobile network's speech quality assessment method described in claim 2-4 any one, it is characterized in that, also comprise:
The first access failure threshold value N0, the second access failure threshold value N1, the 3rd access failure threshold value N2 and the 4th access failure threshold value N3 are set, N0 < N1 < N2 < N3; The first number of dropped calls threshold value M0, the second number of dropped calls threshold value M1, the 3rd number of dropped calls threshold value M2 and the 4th number of dropped calls threshold value M3 are set, M0 < M1 < M2 < M3; The first frequency threshold value P0 of poor quality, the second frequency threshold value P1 of poor quality, the 3rd frequency threshold value P2 of poor quality and the 4th frequency threshold value P3 of poor quality are set, P0 < P1 < P2 < P3;
As A < N0, access procedure quality is excellent; As N0 < A < N1, access procedure quality is good; As N1 < A < N2, during access procedure quality is; As N2 < A < N3, access procedure quality is for poor;
As B < M0, keep-process quality is excellent; As M0 < B < M1, keep-process quality is good; As M1 < B < M2, during keep-process quality is; As M2 < B < M3, keep-process quality is for poor;
As C < P0, complete procedure quality is excellent; As P0 < C < P1, complete procedure quality is good; As P1 < C < P2, during complete procedure quality is; As P2 < C < P3, complete procedure quality is for poor.
7. mobile network's speech quality assessment method according to claim 6, it is characterized in that, describedly according to described access procedure quality assessment value A, keep-process quality assessment value B, complete procedure quality assessment value C and the 4th assessment algorithm, calculate, the mobile network's speech quality evaluation result D that obtains the allocate event of described designated user comprises:
When access procedure quality, keep-process quality and complete procedure quality are excellent, mobile network's speech quality evaluation result D is excellent; When access procedure quality, keep-process quality and complete procedure quality are good, mobile network's speech quality evaluation result D is good; In access procedure quality, keep-process quality and complete procedure quality are, during mobile network's speech quality evaluation result D is; When access procedure quality, keep-process quality and complete procedure quality are poor, mobile network's speech quality evaluation result D is for poor; When access procedure quality, keep-process quality and complete procedure quality are inconsistent, mobile network's speech quality evaluation result D gets minimum in three.
8. mobile network's speech quality assessment method according to claim 1, is characterized in that, also comprises:
(8) fixed time section, determines that the event in described fixed time section of described designated user is described allocate event;
(9) respectively allocate event described in each is carried out to step (3) to the processing of step (7), obtain mobile network's speech quality evaluation result of the allocate event of described designated user;
(10) mobile network's speech quality evaluation result described in each is calculated according to the 5th assessment algorithm, obtained alone family comprehensive evaluation result.
9. mobile network's speech quality assessment method according to claim 8, is characterized in that, also comprises:
(11) specify other user who is associated with described designated user, repeating step (8) is to step (10), obtains the described alone family comprehensive evaluation result of other user described in each;
(12) all described alone families comprehensive evaluation result is calculated according to the 6th assessment algorithm, obtain customer group comprehensive evaluation result.
10. mobile network's speech quality evaluation device, is characterized in that, comprising:
Data acquisition module, the data relevant to speech business that record for obtaining each equipment of mobile network, each packet is containing a plurality of attributes, and each attribute has property value;
Community set is set up module, for setting up community set according to all attributes of described data, and described community set is divided into access procedure attribute set, keep-process attribute set and complete procedure attribute set, in described community set, the value of each attribute is 0;
Attribute assignment module, for obtaining the data set that described data are relevant to the allocate event of designated user, and carries out assignment according to the property value of described data centralization all properties to the respective attributes in described community set, forms alone family single event property set;
Process assessment module, obtains access procedure quality assessment value for calculating according to the first assessment algorithm of the property value of each attribute of access procedure attribute set and appointment; And calculate and obtain keep-process quality assessment value according to the second assessment algorithm of the property value of each attribute in keep-process attribute set and appointment; According to the 3rd assessment algorithm of the property value of each attribute in complete procedure attribute set and appointment, calculate and obtain complete procedure quality assessment value again;
Event evaluation module, for calculating according to described access procedure quality assessment value, keep-process quality assessment value, complete procedure quality assessment value and the 4th assessment algorithm, obtain mobile network's speech quality evaluation result of the allocate event of described designated user.
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