CN111210816A - Intelligent voice configuration management method and device and electronic equipment - Google Patents
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Abstract
The invention discloses an intelligent voice configuration management method, an intelligent voice configuration management device and electronic equipment, wherein the method comprises the following steps: creating and managing a conversational knowledge base, wherein the conversational knowledge base comprises a plurality of answering voice types; searching a target answering voice type matched with the voice of the current user in the dialect knowledge base; and generating a configuration file according to the target answering voice type. The invention can generate different configuration files through different answering voice types, thereby automatically configuring the voice answering flow, and can also complete the configuration of the user-defined dialogues template through the mode of generating different configuration files through the same answering voice type, and finally realize the effect of quickly customizing the intelligent voice dialogue according to the requirements of application scenes according to the difference of the configuration files. Compared with the prior art, the invention has the advantages of fast customization, cost saving and one machine with multiple purposes.
Description
Technical Field
The invention relates to the technical field of intelligent voice control, in particular to an intelligent voice configuration management method, an intelligent voice configuration management device, electronic equipment and a computer readable medium.
Background
At present, the artificial intelligence technology is rapidly developed, the intelligent voice robot is widely applied, and the related intelligent voice interaction technology mainly comprises the technologies of voice recognition, natural language understanding, dialogue management, natural language generation, voice synthesis and the like and comprehensive application. The flow of natural language understanding, dialogue management and natural language generation is also called as an intelligent dialogue system, and is the core technical difficulty of the whole intelligent voice interaction process.
The conversation of the existing intelligent voice robot is set in advance, so that the conversation process management and configuration are not flexible enough, and a user cannot rapidly customize a conversation scene required by the user according to the requirement of the user. For example, for different application scenarios (e.g., telemarketing robot, hastening robot, etc.), the user needs to configure different intelligent voice robots to complete the conversation. Therefore, there is a need for a technology capable of quickly customizing an intelligent voice dialog according to the requirements of an application scenario.
Disclosure of Invention
The invention aims to solve the technical problem that the intelligent voice conversation can not be quickly customized according to the requirements of application scenes in the prior art.
In order to solve the above technical problem, a first aspect of the present invention provides an intelligent voice configuration management method, where the method includes:
creating and managing a conversational knowledge base, wherein the conversational knowledge base comprises a plurality of answering voice types;
searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
and generating a configuration file according to the target answering voice type.
According to a preferred embodiment of the present invention, the creating a linguistic knowledge base comprises:
creating a semantic configuration rule;
generating a answering voice type according to the semantic configuration rule;
and creating workflow nodes and/or answer modes associated with the answer voice type.
According to a preferred embodiment of the present invention, the target answering voice type matching with the current user voice is searched in the dialect knowledge base according to the semantic configuration rule.
According to a preferred embodiment of the present invention, the conversational knowledge base further comprises workflow nodes associated with the answering voice type, the method further comprising:
creating and managing a conversational workflow database, the conversational workflow database comprising a plurality of workflow nodes;
the generating a configuration file according to the target answering voice type comprises the following steps:
and generating a configuration file according to the workflow node associated with the target answering voice type.
According to a preferred embodiment of the present invention, the creating a conversational workflow database comprises:
configuring a dialect workflow and a corresponding workflow node ID;
generating a configuration file according to the workflow node associated with the target answering voice type comprises:
and generating a configuration file according to the workflow node ID associated with the target answering voice type.
According to a preferred embodiment of the present invention, the tactical knowledge base further includes a dialogue mode associated with the target dialogue phonetic type, and the generating the configuration file according to the target dialogue phonetic type includes:
and generating a configuration file according to the answering mode associated with the target answering voice type.
According to a preferred embodiment of the invention, the method further comprises:
and inputting the configuration file into a voice learning model for training and outputting target voice.
In order to solve the above technical problem, a second aspect of the present invention provides an intelligent voice configuration management apparatus, including:
the system comprises a first creating module, a second creating module and a third creating module, wherein the first creating module is used for creating and managing a conversational knowledge base, and the conversational knowledge base comprises a plurality of answering voice types;
the matching module is used for searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
and the first generation module is used for generating a configuration file according to the target answering voice type.
According to a preferred embodiment of the present invention, the first creating module includes:
the first sub-creation module is used for creating semantic configuration rules;
the first sub-generation module is used for generating a reply voice type according to the semantic configuration rule;
and the second sub-creation module is used for creating the workflow nodes and/or the answering modes related to the answering voice type.
According to a preferred embodiment of the present invention, the matching module is specifically configured to search the target answer voice type matching with the voice of the current user in the conversational knowledge base according to the semantic configuration rule.
According to a preferred embodiment of the present invention, the conversational knowledge base further includes workflow nodes associated with the answering voice type, and the apparatus further includes:
a second creation module for creating and managing a conversational workflow database, the workflow database comprising a plurality of workflow nodes;
and the first generation module is used for generating a configuration file according to the workflow node associated with the target answering voice type.
According to a preferred embodiment of the present invention, the second creating module is specifically configured to configure a conversational workflow and a corresponding workflow node ID;
the first generating module is specifically configured to generate a configuration file according to the workflow node ID associated with the target answer voice type.
According to a preferred embodiment of the present invention, the conversational knowledge base further comprises a dialogue mode associated with the dialogue phonetic type,
the first generating module is used for generating a configuration file according to the answering mode associated with the target answering voice type.
According to a preferred embodiment of the invention, the device further comprises:
and the output module is used for inputting the configuration file into a voice learning model for training and outputting the target voice.
In order to solve the above technical problem, a third aspect of the present invention provides an electronic apparatus comprising:
a processor; and
a memory storing computer executable instructions that, when executed, cause the processor to perform the method described above.
In order to solve the above technical problem, a fourth aspect of the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs that, when executed by a processor, implement the above method.
According to the method and the system, the dialect knowledge base containing a plurality of the answering voice types is created and managed, the configuration file related to the answering voice types can be quickly created and modified according to the requirements of application scenes, the target answering voice types matched with the voice of the current user are searched in the dialect knowledge base, and then the configuration file is generated according to the target answering voice types. The invention can generate different configuration files through different answering voice types, thereby automatically configuring the voice answering flow, and can also complete the configuration of the user-defined dialogues template through the mode of generating different configuration files through the same answering voice type, and finally realize the effect of quickly customizing the intelligent voice dialogue according to the requirements of application scenes according to the difference of the configuration files. Compared with the prior art, the invention has the advantages of fast customization, cost saving and one machine with multiple purposes.
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In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive step.
FIG. 1 is a schematic flow chart of an intelligent voice configuration management method of the present invention;
FIG. 2 is a schematic flow chart of another intelligent voice configuration management method of the present invention;
FIG. 3 is a schematic diagram of the structure of a conversational flow database of the present invention;
FIG. 4 is a schematic diagram of the structure of the conversational knowledge base of the present invention;
FIGS. 5 a-5 b are schematic structural frameworks of two different intelligent voice configuration management devices according to the present invention;
FIG. 6 is a block diagram of an exemplary embodiment of an electronic device in accordance with the present invention;
FIG. 7 is a diagrammatic representation of one embodiment of a computer-readable medium of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention may be embodied in many specific forms, and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art.
The structures, properties, effects or other characteristics described in a certain embodiment may be combined in any suitable manner in one or more other embodiments, while still complying with the technical idea of the invention.
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The same reference numerals denote the same or similar elements, components, or parts throughout the drawings, and thus, a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.
Fig. 1 is a schematic flow chart of an intelligent voice configuration management method provided by the present invention; the method comprises the following steps:
s1, creating and managing a conversational knowledge base,
in the invention, the dialect knowledge base comprises a plurality of answering voice types; the answer voice type is a classification of the user's feedback to the voice question. Different answer voice types are associated with different answers.
For example, different answering voice types may be associated with different workflow nodes, different workflow nodes may be identified by workflow node IDs, one workflow node ID may be associated according to user feedback on voice questions (i.e., answering voice type), each workflow node may be configured to provide verbal feedback on the associated answering voice type, e.g., the answering voice type is "price", and its associated workflow node may be configured to specify a product price, e.g., "3500 dollars". Thus, each conversational feedback is associated with a conversational feedback and workflow node ID, and conversational feedback for the conversational type may be found by the associated workflow node ID.
In addition, different answering voice types may also be associated with different answering styles. Wherein, different answering modes can be identified by answering mode ID. The different answering modes can be specifically on-hook, rebroadcasting of a designated number or preset answering voice.
Specifically, the creating the dialect knowledge base includes:
s11, creating semantic configuration rules;
in the invention, the semantic configuration rule classifies the user voice into different answer voice types according to the semantics, for example, classifying the types of 'kayi', 'good', 'can' into the voice type of 'agree to continue' according to the semantics; classifying "unnecessary" and "existing" into "different" voice types according to semantics.
S12, generating a dialogue voice type according to the semantic configuration rule;
specifically, the user voices are classified through a semantic configuration rule, and different answering voice types are generated according to the basic semantics of each classification. The basic semantic meaning refers to the main meaning of the user's voice in the classification, and the main meaning of "kayi", "good" or "may" is "agree with the continuation".
And S13, creating workflow nodes and/or answering modes associated with the answering voice type.
In the invention, the answering voice type can be associated with the workflow node and/or the answering mode according to the basic semantics. For example, for a user's voice "don't need", "having had a voice type" generate "disagree", the voice type "disagree" may be associated with workflow node 32 and answer mode 2, where the conversational template corresponding to workflow node 32 is "thank you! "answer mode 2 is" on hook ".
The management tactical knowledge base comprises: and adding, editing and deleting the voice answer types in the dialect knowledge base.
In the invention, different associated answers (workflow nodes and/or answer modes) can be configured for the same answer voice type to generate different configuration files, so that different dialect templates are generated to meet different application scenes, and the same user voice can be divided into different answer voice types through different voice configuration rules, so that different configuration files are generated, and different dialect templates are generated to meet different application scenes.
S2, searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
in the present invention, the target answering voice type matching with the current user voice can be searched in the dialect knowledge base according to the semantic configuration rule in step S11.
And S3, generating a configuration file according to the target answering voice type.
Specifically, the configuration file may be generated according to the workflow node and/or the answer mode associated with the target answer voice type. In the present invention, the configuration file may be a regular graph or an Application Programming Interface (API) number, and is directly interfaced with the application program through the API number, where the API number may be preset by a system.
FIG. 2 is a schematic flow chart of another intelligent voice configuration management method according to the present invention; the method comprises the following steps:
s201, creating and managing a conversational workflow database,
in the invention, the dialect workflow database comprises a plurality of workflow nodes; each workflow node corresponds to a conversational feedback and workflow node ID, and one or more workflow nodes form a conversational workflow, in this embodiment, one conversational workflow corresponds to one conversational template.
In this embodiment, creating the conversational workflow database includes: configuring a dialect workflow and a corresponding workflow node ID; one dialect workflow corresponds to one dialect template, one dialect module can be realized by a plurality of workflow nodes, so that one dialect workflow can correspond to one or more workflow node IDs, and one workflow node ID can also appear in a plurality of dialect workflows. The invention can configure different dialect workflows by selecting the workflow node ID and realize the custom configuration of the dialect template. In some application scenes, a custom-configured dialogs template can be directly called to generate a configuration file, and intelligent conversation is completed.
As shown in fig. 3, the conversational workflow database includes a first workflow node, a second workflow node, a third workflow node and a fourth workflow node, wherein, the first workflow node corresponds to the conversational feedback a and the workflow node ID01, the second workflow node corresponds to the conversational feedback b and the workflow node ID02, the third workflow node corresponds to the conversational feedback c and the workflow node ID03, the fourth workflow node corresponds to the conversational feedback d and the workflow node ID04, one conversational workflow R is configured to correspond to the workflow node ID02 and the workflow node ID03, and the other conversational workflow Q corresponds to the workflow node ID02 and the workflow node ID04, the conversational feedback b for workflow node ID02 and the conversational feedback C for workflow node ID03 generate a conversational module R corresponding to conversational workflow R, and the conversational feedback b for workflow node ID02 and the conversational feedback d for workflow node ID04 generate a conversational template Q corresponding to conversational workflow Q.
The invention can also number according to different dialogies workflow of application scenes, and correspond to different application scenes through different dialogies workflow numbers, for example, in fig. 3, the number of the dialogies workflow R is set to correspond to a telemarketing robot, and the number of the dialogies workflow Q is set to correspond to a payment-urging robot.
In the present invention, the management speech operation flow database comprises: adding, editing, deleting a conversational workflow, displaying node data of the conversational workflow, and the like, wherein the editing of the conversational workflow comprises: add, edit, and delete workflow node data, and the like.
S202, creating and managing a dialogies knowledge base,
in this embodiment, the conversational knowledge base includes a semantic configuration rule, a plurality of answer voice types, and workflow nodes associated with the answer voice types; different answering voice types are associated with different workflow nodes. Each workflow node corresponds to a conversational feedback and workflow node ID. Therefore, in one session, the user voice is sequentially classified into a plurality of different answering voice types according to the voice configuration rule, and corresponding conversational feedback can be obtained according to workflow nodes associated with the plurality of answering voice types. The invention can automatically configure the answering process for different answering voice types, and realizes the automatic configuration and management of the voice answering process.
As shown in fig. 4, the conversational knowledge base includes a first answer voice type, a second answer voice type, a third answer voice type, a fourth answer voice type, and a fifth answer voice type, where the first answer voice type is associated with workflow node ID11, the second answer voice type is associated with workflow node ID12, the third answer voice type is associated with workflow node ID13, the fourth answer voice type is associated with workflow node ID14, and the fifth answer voice type is associated with workflow node ID15, and in a section of conversation, if the user voices are sequentially classified into the first answer voice type, the third answer voice type, and the fourth answer voice type, a dialogue flow is sequentially generated by workflow node ID11, workflow node ID13, and workflow node ID 14.
Specifically, the creating the dialect knowledge base includes:
s31, creating semantic configuration rules;
s32, generating a dialogue voice type according to the semantic configuration rule;
and S33, creating the workflow nodes associated with the answering voice type.
The steps S31 to S33 correspond to the steps S11 to S13, respectively, and are not described herein again.
The management tactical knowledge base comprises: and adding, editing and deleting the voice answer types in the dialect knowledge base.
S203, searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
and S204, generating a configuration file according to the target answering voice type.
The steps S303 to S304 correspond to the steps S2 to S3, respectively, and are not described herein again.
And S205, inputting the configuration file into a voice learning model for training and outputting the target voice.
In this embodiment, the configuration file may be used as a training set of a speech learning mode to train a speech learning model, and may also be used as an input parameter of the speech learning model to output a target speech for human-computer speech interaction.
Fig. 5a is a schematic structural framework diagram of an intelligent voice configuration management device according to the present invention, and as shown in fig. 5a, the device includes: a first creation module 51, a matching module 52 and a first generation module 53; wherein:
a first creating module 51 for creating and managing a conversational knowledge base, the conversational knowledge base comprising a plurality of dialogue voice types;
a matching module 52, configured to search the conversational knowledge base for a target answer voice type matching the current user voice;
and the first generating module 53 is configured to generate a configuration file according to the target answering voice type.
Illustratively, the first creating module 51 includes:
a first sub-creation module 511, configured to create a semantic configuration rule;
a first sub-generating module 512, configured to generate a dialogue voice type according to the semantic configuration rule;
a second sub-creation module 513, configured to create a workflow node and/or a reply mode associated with the reply voice type.
The matching module 52 is specifically configured to search the target answer voice type matched with the voice of the current user in the conversational knowledge base according to the semantic configuration rule.
Fig. 5b is a schematic structural framework diagram of another intelligent voice configuration management device of the present invention, as shown in fig. 5b, the device includes: a first creating module 51, a second creating module 52, a matching module 53, a first generating module 54, and an output module 55; wherein:
a first creating module 51 for creating and managing a conversational knowledge base, the conversational knowledge base comprising a plurality of conversational speech types, workflow nodes associated with the conversational speech types and/or conversational modalities associated with the conversational speech types.
A second creation module 52 for creating and managing a conversational workflow database, the workflow database comprising a plurality of workflow nodes; the second creating module 52 is specifically configured to configure a conversational workflow and a corresponding workflow node ID;
a matching module 53, configured to search the conversational knowledge base for a target answer voice type matching the current user voice;
the first generating module 54 is specifically configured to generate a configuration file according to the workflow node ID and/or the answer mode associated with the target answer voice type.
And the output module 55 is used for inputting the configuration file into a voice learning model for training and outputting the target voice.
Those skilled in the art will appreciate that the modules in the above-described embodiments of the apparatus may be distributed as described in the apparatus, and may be correspondingly modified and distributed in one or more apparatuses other than the above-described embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as an implementation in physical form for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 6 is a block diagram of an exemplary embodiment of an electronic device according to the present invention. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the electronic device 500 of the exemplary embodiment is represented in the form of a general-purpose data processing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different electronic device components (including the storage unit 620 and the processing unit 610), a display unit 640, and the like.
The storage unit 620 stores a computer readable program, which may be a code of a source program or a read-only program. The program may be executed by the processing unit 610 such that the processing unit 610 performs the steps of various embodiments of the present invention. For example, the processing unit 610 may perform the steps shown in fig. 1 or fig. 2.
The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203. The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: operating the electronic device, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 600 may also communicate with one or more external devices 300 (e.g., keyboard, display, network device, bluetooth device, etc.), enable a user to interact with the electronic device 600 via the external devices 600, and/or enable the electronic device 600 to communicate with one or more other data processing devices (e.g., router, modem, etc.). Such communication can occur via input/output (I/O) interfaces 650, and can also occur via network adapter 660 with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet). The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in FIG. 6, other hardware and/or software modules may be used in the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID electronics, tape drives, and data backup storage electronics, among others.
FIG. 7 is a schematic diagram of one computer-readable medium embodiment of the present invention. As shown in fig. 7, the computer program may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic device, apparatus, or device that is electronic, magnetic, optical, electromagnetic, infrared, or semiconductor, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. The computer program, when executed by one or more data processing devices, enables the computer-readable medium to implement the above-described method of the invention, namely: creating and managing a conversational knowledge base, wherein the conversational knowledge base comprises a plurality of answering voice types; searching a target answering voice type matched with the voice of the current user in the dialect knowledge base; and generating a configuration file according to the target answering voice type.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a data processing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution electronic device, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the present invention can be implemented as a method, an apparatus, an electronic device, or a computer-readable medium executing a computer program. Some or all of the functions of the present invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP).
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (10)
1. An intelligent voice configuration management method, the method comprising:
creating and managing a conversational knowledge base, wherein the conversational knowledge base comprises a plurality of answering voice types;
searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
and generating a configuration file according to the target answering voice type.
2. The method of claim 1, wherein creating the linguistic knowledge base comprises:
creating a semantic configuration rule;
generating a answering voice type according to the semantic configuration rule;
and creating workflow nodes and/or answer modes associated with the answer voice type.
3. The method according to claims 1-2, wherein the target answer voice type matching with the current user voice is searched in the dialect knowledge base according to the semantic configuration rule.
4. The method of claims 1-3, wherein the conversational knowledge base further comprises workflow nodes associated with the conversational speech class, the method further comprising:
creating and managing a conversational workflow database, the conversational workflow database comprising a plurality of workflow nodes;
the generating a configuration file according to the target answering voice type comprises the following steps:
and generating a configuration file according to the workflow node associated with the target answering voice type.
5. The method of claims 1-4, wherein creating the conversational workflow database comprises:
configuring a dialect workflow and a corresponding workflow node ID;
generating a configuration file according to the workflow node associated with the target answering voice type comprises:
and generating a configuration file according to the workflow node ID associated with the target answering voice type.
6. The method of claims 1-5, wherein the conversational knowledge base further comprises a dialogue mode associated with the target dialogue phonetic type, and wherein generating a profile based on the target dialogue phonetic type comprises:
and generating a configuration file according to the answering mode associated with the target answering voice type.
7. The method of claims 1-6, further comprising:
and inputting the configuration file into a voice learning model for training and outputting target voice.
8. An intelligent voice configuration management apparatus, the apparatus comprising:
the system comprises a first creating module, a second creating module and a third creating module, wherein the first creating module is used for creating and managing a conversational knowledge base, and the conversational knowledge base comprises a plurality of answering voice types;
the matching module is used for searching a target answering voice type matched with the voice of the current user in the dialect knowledge base;
and the first generation module is used for generating a configuration file according to the target answering voice type.
9. An electronic device, comprising:
a processor; and
a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-7.
10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-7.
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