CN110769124A - Electric power marketing customer communication system - Google Patents
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Abstract
The invention discloses a power marketing customer communication system which utilizes technologies such as voice recognition, natural language understanding and voice synthesis to respectively realize the transcription of user voice data, the analysis of user intention, knowledge feedback voice synthesis broadcasting and the like, and is matched with an intelligent voice technology library extremely suitable for marketing work characteristics of power grid enterprises to further realize voice interaction between intelligent services and users. The method can well replace the work with high business success rate, and is mainly applied to typical scenes such as customer electric charge reminding and payment urging, data checking, personalized service and the like. Replace 80% of artificial telephones, and achieve the effects of reducing cost, improving efficiency, improving service and benefiting management.
Description
Technical Field
The invention relates to a power marketing customer communication system, and belongs to the technical field of artificial intelligence voice.
Background
At present, national grid company is accelerating to build ubiquitous electric power thing networking, and the development of the integration of "the big cloud thing moves intelligence" technique and marketing business has become inevitable trend, and all kinds of novel marketing services will emerge constantly on this basis, but these final falling to the ground of service need timely acquireing information of user and good service communication, because traditional manpower communication exists with high costs, inefficiency, the big short slab of risk, and the science and technology development has been discomforted. Therefore, the development of the intelligent voice system which accords with the working characteristics and the flow of the power enterprise and the typical customer service scene has very important application significance.
Disclosure of Invention
The invention aims to provide a power marketing customer communication system, and aims to solve the problems that power grid enterprises are wide in customer number and different in demand, and a large amount of marketing service work is too dependent on manpower. The intelligent voice technology is applied to typical scenes such as electric charge reminding and urging, customer data checking, personalized service and the like, various service information under the internet of things and the 'last kilometer' of a user can be quickly communicated, information can be accurately transmitted in real time, and the intelligent voice system can well replace the work of relatively simple processes, repeated operation machinery and massive target customers.
The purpose of the invention is realized by the following technical scheme:
an electric power marketing customer communication system, wherein intelligent voice outbound system combines with IVR system to realize the interactive flow of intelligent voice, outbound questionnaire and response knowledge of the intelligent voice outbound system follow the rules of the existing service system, and carry on the intelligent response according to the response knowledge in the existing service system; the intelligent voice outbound system is combined with the current outbound system, an outbound list is screened by a rule set in the existing outbound system, a user name list conforming to the intelligent outbound flow is pushed to the intelligent voice outbound system for outbound, a service flow which cannot be completed in the intelligent voice outbound system can also be automatically transferred to an artificial seat in the existing outbound system for outbound, and outbound data is recorded;
the intelligent voice outbound system consists of a VUI service layer, a core layer, background operation and maintenance management and data service; the VUI service layer is used for realizing the flow design and the session logic design of intelligent voice interaction and realizing the butt joint with a service system through interface service; the core layer is used for providing voice capability support for intelligent voice interaction services, can realize recognition transcription and semantic understanding analysis of user voice data, and can convert character information in a service knowledge base into voice data for real-time broadcasting; the core layer comprises four parts, namely MRCP transfer service, voice recognition service, semantic understanding service and voice synthesis service; operation and maintenance management and database: the functions of managing an outbound flow and data, monitoring the running state of an engine, displaying a voice data processing result and searching a recorded voice tune are supported; statistics and report analysis are carried out on system operation parameters and various data operation results; supporting the management work of user authority and authorization;
MRCP service, which realizes the interface of intelligent voice navigation and IVR platform, MRCP server receives the user voice data from IVR platform, identifies and understands, and sends the identification result (menu node information) to IVR platform, and the IVR platform carries out relevant service operation; meanwhile, the MRCP server also receives the text transmitted by the IVR platform, and the voice synthesized by the TTS engine is provided to the IVR platform, and the voice is played to the user in the service flow;
the scheduling service mainly comprises: the system comprises an Apache Web server, an Audiokeeper transfer module, a Tomcat Web server and a TTS proxy module;
apache Web server: the Web server is based on Apache, mainly realizes the processing of HTTP query requests by using a PHP technology, realizes forwarding and redirection and has extremely high concurrency and processing capacity; the Server is responsible for forwarding the identification request from the MRCP Server, forwarding the identification result to the understanding module after obtaining the identification result, and finally returning the identification and understanding result to the MRCP Server;
audiokeeper transfer module: the transfer service adopts a mode of TCP direct connection, and mainly realizes the transfer function of voice data:
1) continuously receiving voice data from a client;
2) continuously sending the data to a voice recognition server side to finally obtain a recognition result;
the essence of the Audiokeeper is that a plurality of post requests from the front end are spliced into a data packet, and the data packet is in long connection with the rear end, and the Audiokeeper is simultaneously a transfer module and is connected with the Decoder through a socket; in addition, the database is also operated through a network interface; the interaction aspect of the Audiokeeper is responsible for receiving the voice data uploaded by the Apache/PHP and uploading the recognition result returned by the Decoder to the Apache/PHP; the Audiokeeper transfer module is also responsible for load balancing of the Decoder; in the aspect of exchange with a database, the method mainly stores the received voice stream data and the returned recognition result into the database; in addition, the system is also responsible for the authentication of user authorization;
tomcat Web server:
the understanding service is built on a Tomcat server, an open understanding service entrance is realized by using a Java technology, and an understanding task is completed;
TTS proxy module:
the TTS Proxy is a speech synthesis forwarding module and is responsible for forwarding a TTS request, distributing a task to an idle TTS Combiner, completing a synthesis task and sending a synthesized speech sub-packet back to an upper layer module;
the speech/semantic understanding server cluster includes three classes: a speech recognition Server Decoder, a speech synthesis Server TTSCombiner and a semantic understanding Server Understand Server;
the voice recognition server is responsible for receiving the voice input of the user submitted by the transfer server, decoding and recognizing the voice and finally returning the recognition result to the transfer server;
the voice synthesis server is responsible for synthesizing the text content to be fed back to the client into a sound stream or a sound file, and then playing back the sound stream or the sound file to the client;
the semantic understanding server mainly understands the text content, particularly the content of voice recognition, analyzes named entity information and intention information of a user in the text content and particularly the content of voice recognition to provide the information for a human-computer interaction system (such as an intelligent voice navigation system) to perform subsequent operations;
the speech recognition and semantic understanding server cluster is also closely related to the application service system. The application service system provides the contents to be processed (including linguistic data, grammar and word list of voice recognition, text contents to be synthesized, semantic database contents and the like) for the voice processing server group; in the actual online implementation process, an interface is well defined, seamless connection between the two is ensured, and the functions of voice recognition, synthesis and semantic understanding are ensured to be accurately and fully exerted;
operation and maintenance management and database:
the system can support the management of an outbound flow, the display of a voice data processing result and a recording, tuning and searching function, also support the statistics of system operation parameters and various data operation results, and also support the management work of users and authorities; the database mainly provides functions of authorization management, flow monitoring and voice data storage; in the aspect of authorization management, the database server provides management functions for user profiles, including registration, statistics, modification and deletion operations of the user profiles; the system records all the user authorization numbers of the service so as to be used as the basis for providing service and charging for the user; in the aspect of flow monitoring, a database server records the sending and receiving conditions of a data packet requested by a user each time and the time information of each node requested at this time; according to the information, the flow condition of the online system can be conveniently mastered, and the evaluation and the improvement of the service quality of a manager are facilitated; in the aspect of voice data storage, the database server can store voice data and corresponding recognition results of each conversation of a user, and manual marking is carried out by utilizing the voice data and the recognition results, so that the recognition rate of the voice recognition engine is further improved.
The working method of the intelligent voice outbound system of the electric power marketing customer communication system comprises the following steps:
1. actively calling a user, connecting a call, and playing guidance opening white voice by the system; the playing voice can be pre-recorded data, or mixed voice through TTS synthesis service or the combination of the two;
2. after the call is connected, the call center sends a starting identification command to the MRCP Server, and the MRCP Server starts to detect whether the client starts speaking;
3, MRCP Server detects the voice, starts to recognize, and ends the open field white voice playing at the same time;
the MRCP Server completes the recognition and returns the recognition and understanding result at the same time;
5. the intelligent voice outbound system determines the next process according to the understanding result, plays the corresponding prompt voice to the client and simultaneously returns to the step 2 to wait for the voice instruction of the client;
6. the intelligent voice outbound system work ending condition comprises that a client actively hangs up, changes into manual work, changes into specific service processing and waits overtime.
Compared with the prior art, the invention has the beneficial effects that: the system utilizes the technologies of voice recognition, natural language understanding, voice synthesis and the like to respectively realize the transcription of user voice data, the analysis of user intention, knowledge feedback voice synthesis broadcasting and the like, and is matched with an intelligent voice technology library which is extremely suitable for the marketing work characteristics of power grid enterprises to further realize the voice interaction between intelligent services and users. The method can well replace the work with high business success rate, and is mainly applied to typical scenes such as customer electric charge reminding and payment urging, data checking, personalized service and the like. Replace 80% of artificial telephones, and achieve the effects of reducing cost, improving efficiency, improving service and benefiting management.
Drawings
FIG. 1 is a screenshot of a full-process monitoring interface of the present invention;
FIG. 2 is a screenshot of a label rating interface of the present invention;
FIG. 3 is a screenshot of a data analysis interface of the present invention;
FIG. 4 is an overall architecture diagram of the power marketing customer communication system of the present invention;
FIG. 5 is an intelligent outbound flow diagram of the present invention;
FIG. 6 is a data flow diagram of the present invention;
FIG. 7 is a schematic diagram of the working method of the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
The invention has the technical characteristics that:
1. intelligent dialogue
The system has the core advantages that the system has a sub-scene intelligent voice technology library and a data management mode with corresponding intellectual property rights, can intelligently respond to users, supports an endpoint detection (VAD) function, can immediately interrupt the current voice playing of the robot, enters the intelligent interruption mode, firstly stops calling a corresponding scene configuration flow and a corresponding voice technology, guides the users to return to the original flow. The response is quick, and the customer experience is good.
2. Full-process monitoring
As shown in fig. 1, a background manager can monitor the task state, and can perform call data query, export, and statistics.
3. Automatic recording
The system telephone recording is stored in the cloud, so that the calling at any time is supported, and the recording can be accurately converted into characters.
4. Precision grading
As shown in fig. 2, the data calculation function can judge the user tags in the whole process, accurately lock the target client, and assist in mining the potential value of the client.
5. Data analysis
As shown in FIG. 3, task data is presented clearly to assist in enterprise query management. And the call data and the client state are mastered at any time.
6. Human-machine collaboration
In the process of the robot call, the on-line switching of the call to manual customer service without hanging up is supported, the dialog recording text is displayed by a screen flicking mode, the keywords are highlighted, and the manual operation can be conveniently and rapidly switched into the dialog.
Perfect combination of TTS synthesized speech and artificial recording
The variable part adopts TTS to synthesize voice, the constant part adopts manual recording, two sound sources are optimized and then synthesized into a section of audio frequency to be played, and the whole voice is smooth.
Fig. 4 is a diagram showing the overall architecture of the power marketing customer communication system.
The intelligent voice outbound system needs to be combined with the IVR system to realize an intelligent voice interaction process, and simultaneously, an outbound questionnaire and response knowledge of the intelligent outbound system need to follow the rules of the existing business system and carry out intelligent response according to the response knowledge in the existing business system. Meanwhile, the intelligent outbound system needs to be combined with the current outbound system for use, an outbound list can be screened through rules set in the existing outbound system, a user name list conforming to the intelligent outbound flow is pushed to the intelligent outbound system for outbound, a service flow which cannot be completed in the intelligent outbound system can be automatically transferred to an artificial seat in the existing outbound system for outbound, and outbound data is recorded.
The intelligent outbound system comprises four parts of a VUI service layer, a core layer, background operation and maintenance management and data service, and the functions and the specific description of each part are as follows:
VUI service layer:
the method is used for realizing the flow design and the conversation logic design of intelligent voice interaction and realizing the butt joint with a business system through interface service.
Core layer:
the voice recognition and translation system is used for providing voice capability support for intelligent voice interaction services, can realize recognition and translation and semantic understanding analysis of user voice data, and can convert text information in a service knowledge base into voice data for real-time broadcasting. The core layer mainly includes four parts, which are MRCP relay service, speech recognition service, semantic understanding service, and speech synthesis service, and the specific introduction of each module is described in the following sections.
Operation and maintenance management and database: the system can support the functions of managing an outbound flow and data, monitoring the running state of an engine, displaying a voice data processing result, listening and searching a recorded sound, and the like, and also support the statistics and report analysis of system running parameters and running results of various data. Management of user rights and authorizations is also supported.
Functional description of each module:
the specific functions of each module are described as follows:
MRCP service
MRCP Server, MRCP service, realizes the interface of intelligent voice navigation and IVR platform, MRCP Server receives the user voice data from IVR platform, identifies and understands, and sends the identification result (menu node information) to IVR platform, and the IVR platform carries out relevant service operation. Meanwhile, the MRCP server also receives the text transmitted by the IVR platform, provides the voice synthesized by the TTS engine to the IVR platform, and plays the voice to the user in the service flow.
Transfer scheduling service
The scheduling service mainly comprises: the system comprises an Apache Web server, an Audiokeeper transfer module, a Tomcat Web server, a TTS proxy module and the like.
Apache Web server:
the Web server is based on Apache, mainly realizes the processing of HTTP query requests by using a PHP technology, realizes forwarding and redirection, and has extremely high concurrency and processing capabilities. The Server is responsible for forwarding the identification request from the MRCP Server, forwarding the identification result to the understanding module after obtaining the identification result, and finally returning the identification and understanding result to the MRCP Server together.
Audiokeeper transfer module:
the transfer service adopts a mode of TCP direct connection, and mainly realizes the transfer function of voice data:
1. voice data from the client is continuously received.
2. And continuously sending the data to a voice recognition server side to finally obtain a recognition result.
The essence of Audiokeeper is to put multiple post requests from the front end together into one packet and maintain a long connection with the back end. The Audiokeeper is also a transfer module and is connected with the Decoder through a socket. In addition, the database is also operated through a network interface. And the interaction aspect of the Audiokeeper is responsible for receiving the voice data uploaded by the Apache/PHP and uploading the recognition result returned by the Decoder to the Apache/PHP.
In addition, the module is also responsible for the load balancing of the Decoder. In the aspect of exchange with the database, the received voice stream data and the returned recognition result are mainly stored in the database. In addition, the system is also responsible for the authentication of user authorization.
Tomcat Web server:
the understanding service is built on a Tomcat server, and an open understanding service entrance is realized and an understanding task is completed by using Java technology.
TTS proxy module:
the TTS Proxy is a speech synthesis forwarding module and is responsible for forwarding a TTS request, distributing a task to an idle TTS Combiner, completing a synthesis task, and sending a synthesized speech sub-packet back to an upper layer module.
Speech recognition/synthesis/understanding service
The speech/semantic understanding server cluster mainly comprises three types: a speech recognition Server Decoder, a speech synthesis Server TTS Combiner and a semantic understanding Server Understand Server.
The voice recognition server is responsible for receiving the voice input of the user submitted by the transit server, decoding and recognizing the voice, and finally returning the recognition result to the transit server. The recognition rate of the system should keep the characteristics of high recognition accuracy and quick response.
The voice synthesis server is responsible for synthesizing the text content required to be fed back to the client into a sound stream or a sound file, and then the sound stream or the sound file can be played back to the client.
The semantic understanding server mainly understands the text content, particularly the content of voice recognition, analyzes named entity information and intention information of a user in the text content, and provides the information for a human-computer interaction system (such as an intelligent voice navigation system) to perform subsequent operations.
It is worth mentioning that the speech recognition and semantic understanding server farm is also closely related to the application business system. The application service system provides the speech processing server group with the contents to be processed (including the linguistic data, grammar and word list of speech recognition, the text contents to be synthesized, the semantic database contents and the like). In the actual online implementation process, an interface is well defined, seamless connection between the two is guaranteed, and functions of voice recognition, synthesis and semantic understanding are guaranteed to be accurately and fully exerted.
Operation and maintenance management and database:
the system can support the functions of management of an outbound flow, display of a voice data processing result, record listening and retrieval and the like, statistics of system operation parameters and various data operation results, and management work of users and authorities. The database mainly provides functions of authorization management, flow monitoring and voice data storage. In the aspect of authorization management, the database server provides management functions for user profiles, including registration, statistics, modification, deletion and the like of the user profiles. The system records all the user authorization numbers of the service, so as to be used as the basis for providing service and charging for the user. The information of the user profile should be as detailed as possible, capable of supporting the needs of various services developed on the platform, and supporting off-site user access through a networked interface.
In the aspect of flow monitoring, the database server records the sending and receiving conditions of the data packet requested by each user and the time information of each node requested at this time. According to the information, the traffic condition of the online system can be conveniently mastered, and the evaluation and the improvement of the service quality of a manager are facilitated. In terms of voice profile storage, the database server may store voice data and corresponding recognition results for each session of the user. By using the voice data and the recognition result, manual marking can be carried out, and the recognition rate of the voice recognition engine is further improved.
The implementation method of the invention comprises the following steps:
through the voice recognition (ASR) and voice synthesis (TTS) technologies of the industry center, the intelligent outbound robot can communicate with the set target client according to the preset dialect. The business target of the outbound is achieved through multi-turn conversation and conversational guidance. The telephone can be actively called out, multiple rounds of voice communication can be carried out with the user, and the telephone can successfully call out in the fields of electric charge reminding and payment prompting, customer data checking, personalized service and the like instead of most manual work. The invention can carry out the electric bill reminding by calling out the defaulting list and the account information of the marketing system through the telephone and combining with the mature reminding call-up operation, generates the interactive result of the person to be reminded and the robot in real time and can follow up with the manual work in real time according to the business condition.
Fig. 5 shows an intelligent outbound flow chart of the present invention, wherein a company outbound displays a list of numbers: and a pre-configured outbound display number pool is provided for the intelligent outbound. Robotic surgery list: the method is a preset power outbound business conversation template. And (3) creating a task: intelligent outbound task creation is carried out through task management, and explicit numbers, outbound calling techniques, outbound robot number, outbound time period control and the like are selected. Importing client information: in order to import the called contact information, such as information of residents who overdue electricity, in the task interface, incomplete tasks can acquire the information of the rest contacts through retrieval. And (3) starting a task: for intelligent outbound task initiation, a pause/delete task may be performed after initiation. And (3) carrying out a task: and after the intelligent outbound task starts, voice transcription is carried out in real time, the call recording and the call record uploading are completed and are stored in a database, and the call result is called back to the service system for real-time display. And (3) completing the task: and after the task is completed, pushing a task completion result including a task clue, task details, conversation details and the like through a callback interface.
FIG. 6 is a data flow diagram of the present invention; the intelligent voice outbound system work flow mainly comprises:
1. actively calling a user, connecting a call, and playing guidance opening white voice by the system; the played voice can be pre-recorded data, or mixed voice through TTS synthesis service or the combination of the two.
2. After the call is connected, the call center sends a start identification command to the MRCP Server, and the MRCP Server starts to detect whether the client starts speaking.
And 3, the MRCP Server detects the voice, starts to recognize and simultaneously ends the playing of the open field white voice.
And 4, the MRCP Server completes the recognition and returns the recognition and understanding results at the same time.
And 5, the AI outbound call determines the next process according to the understanding result, plays corresponding prompt voice to the client and returns to the step 2 to wait for the voice instruction of the client.
6. The intelligent voice outbound call work ending condition comprises client active hang-up, manual transfer, specific service processing transfer, overtime waiting and the like.
The operation is as follows:
the invention is applied to the reminding of the electric bill, is a perfect solution aiming at the traditional manual reminding which wastes time and labor and has lower effect, can efficiently and reasonably remind and urge money for the clients who drag the arrearage, and can flexibly deal with the universal difficulty and the change of the clients.
The robot is mainly responsible for: the work with high session success rate such as first touch, loss of contact checking and the like is mainly applied to the payment reminding of the first touch of a client and the 'loss of contact checking' work intentionally delinquent.
The conversational scenario is as follows:
the system is an intelligent voice system with industry characteristics developed by a marketing front-line staff aiming at a daily typical customer service communication scene after deeply knowing marketing working characteristics and flow of a power grid enterprise, and has the core advantages of a sub-scene intelligent voice technology library with corresponding intellectual property rights and a data management mode. At present, the scene-based intelligent speech technology library is divided into: the system comprises an electric charge reminding function, an electric charge payment prompting function, an information informing function, a data checking function, an individualized service function and a comprehensive energy service popularization function. The core competitiveness of the system lies in that the dialect library is stable and mature, the marketing work scene of a power grid enterprise is extremely met, the applicability rate is high, and the popularization is strong.
TABLE 1 application scenario-Power supply electric charge urging call operation (resident) not overdue
TABLE 2 application scenario-Power supply electric charge urging call operation (resident) overdue
The electric power collection service implementation method is shown in fig. 7:
And 2, acquiring the contact person through the service system to establish an outbound task.
And 4, finishing the call, wherein the finishing can be manual switching, hanging up of the called party, overtime waiting and the like.
And 5, data callback, call result, call recording and call text callback to a service system for statistics and archiving.
In the future, with the help of the high-speed construction of ubiquitous power internet of things, the rapid development of new businesses such as comprehensive energy sources and the like, the system can develop comprehensive energy service expansion such as electric vehicle popularization, photovoltaic industry propaganda, combined cooling, heating and power supply and the like, and services such as power market user policy notification and transaction matching and the like for target customers through the functions of accurate label classification and big data analysis.
In addition to the above embodiments, the present invention may have other embodiments, and any technical solutions formed by equivalent substitutions or equivalent transformations fall within the scope of the claims of the present invention.
Claims (2)
1. A power marketing customer communication system is characterized in that an intelligent voice outbound system is combined with an IVR system to realize an intelligent voice interaction process, an outbound questionnaire and response knowledge of the intelligent voice outbound system follow the rules of the existing service system, and intelligent response is carried out according to the response knowledge in the existing service system; the intelligent voice outbound system is combined with the current outbound system, an outbound list is screened by a rule set in the existing outbound system, a user name list conforming to the intelligent outbound flow is pushed to the intelligent voice outbound system for outbound, a service flow which cannot be completed in the intelligent voice outbound system can also be automatically transferred to an artificial seat in the existing outbound system for outbound, and outbound data is recorded;
the intelligent voice outbound system consists of a VUI service layer, a core layer, background operation and maintenance management and data service; the VUI service layer is used for realizing the flow design and the session logic design of intelligent voice interaction and realizing the butt joint with a service system through interface service; the core layer is used for providing voice capability support for intelligent voice interaction services, can realize recognition transcription and semantic understanding analysis of user voice data, and can convert character information in a service knowledge base into voice data for real-time broadcasting; the core layer comprises four parts, namely MRCP transfer service, voice recognition service, semantic understanding service and voice synthesis service; operation and maintenance management and database: the functions of managing an outbound flow and data, monitoring the running state of an engine, displaying a voice data processing result and searching a recorded voice tune are supported; statistics and report analysis are carried out on system operation parameters and various data operation results; supporting the management work of user authority and authorization;
MRCP service, which realizes the interface of intelligent voice navigation and IVR platform, MRCP server receives the user voice data from IVR platform, identifies and understands, and sends the identification result (menu node information) to IVR platform, and the IVR platform carries out relevant service operation; meanwhile, the MRCP server also receives the text transmitted by the IVR platform, and the voice synthesized by the TTS engine is provided to the IVR platform, and the voice is played to the user in the service flow;
the scheduling service mainly comprises: the system comprises an Apache Web server, an Audiokeeper transfer module, a Tomcat Web server and a TTS proxy module;
apache Web server: the Web server is based on Apache, mainly realizes the processing of HTTP query requests by using a PHP technology, realizes forwarding and redirection and has extremely high concurrency and processing capacity; the Server is responsible for forwarding the identification request from the MRCP Server, forwarding the identification result to the understanding module after obtaining the identification result, and finally returning the identification and understanding result to the MRCP Server;
audiokeeper transfer module: the transfer service adopts a mode of TCP direct connection, and mainly realizes the transfer function of voice data:
1) continuously receiving voice data from a client;
2) continuously sending the data to a voice recognition server side to finally obtain a recognition result;
the essence of the Audiokeeper is that a plurality of post requests from the front end are spliced into a data packet, and the data packet is in long connection with the rear end, and the Audiokeeper is simultaneously a transfer module and is connected with the Decoder through a socket; in addition, the database is also operated through a network interface; the interaction aspect of the Audiokeeper is responsible for receiving the voice data uploaded by the Apache/PHP and uploading the recognition result returned by the Decoder to the Apache/PHP; the Audiokeeper transfer module is also responsible for load balancing of the Decoder; in the aspect of exchange with a database, the method mainly stores the received voice stream data and the returned recognition result into the database; in addition, the system is also responsible for the authentication of user authorization;
tomcat Web server:
the understanding service is built on a Tomcat server, an open understanding service entrance is realized by using a Java technology, and an understanding task is completed;
TTS proxy module:
TTS Proxy is a speech synthesis forwarding module and is responsible for forwarding TTS requests, distributing tasks to idle TTSCombiners, completing synthesis tasks and sending synthesized speech sub-packets back to an upper layer module;
the speech/semantic understanding server cluster includes three classes: a speech recognition Server Decoder, a speech synthesis Server TTSCombiner and a semantic understanding Server Understand Server;
the voice recognition server is responsible for receiving the voice input of the user submitted by the transfer server, decoding and recognizing the voice and finally returning the recognition result to the transfer server;
the voice synthesis server is responsible for synthesizing the text content to be fed back to the client into a sound stream or a sound file, and then playing back the sound stream or the sound file to the client;
the semantic understanding server mainly understands the text content, particularly the content of voice recognition, analyzes named entity information and intention information of a user in the text content and particularly the content of voice recognition to provide the information for a human-computer interaction system (such as an intelligent voice navigation system) to perform subsequent operations;
the speech recognition and semantic understanding server cluster is also closely related to the application service system. The application service system provides the contents to be processed (including linguistic data, grammar and word list of voice recognition, text contents to be synthesized, semantic database contents and the like) for the voice processing server group; in the actual online implementation process, an interface is well defined, seamless connection between the two is ensured, and the functions of voice recognition, synthesis and semantic understanding are ensured to be accurately and fully exerted;
operation and maintenance management and database:
the system can support the management of an outbound flow, the display of a voice data processing result and a recording, tuning and searching function, also support the statistics of system operation parameters and various data operation results, and also support the management work of users and authorities; the database mainly provides functions of authorization management, flow monitoring and voice data storage; in the aspect of authorization management, the database server provides management functions for user profiles, including registration, statistics, modification and deletion operations of the user profiles; the system records all the user authorization numbers of the service so as to be used as the basis for providing service and charging for the user; in the aspect of flow monitoring, a database server records the sending and receiving conditions of a data packet requested by a user each time and the time information of each node requested at this time; according to the information, the flow condition of the online system can be conveniently mastered, and the evaluation and the improvement of the service quality of a manager are facilitated; in the aspect of voice data storage, the database server can store voice data and corresponding recognition results of each conversation of a user, and manual marking is carried out by utilizing the voice data and the recognition results, so that the recognition rate of the voice recognition engine is further improved.
2. The method of claim 1, wherein the method comprises:
1) actively calling a user, connecting a call, and playing guidance opening white voice by the system; the playing voice can be pre-recorded data, or mixed voice through TTS synthesis service or the combination of the two;
2) after the call is connected, the call center sends a starting identification command to the MRCP Server, and the MRCP Server starts to detect whether the client starts speaking;
3) the MRCP Server detects the voice, starts to recognize and ends the playing of the open field white voice at the same time;
4) the MRCP Server completes the recognition and returns the recognition and understanding results at the same time;
5) the intelligent voice outbound system determines the next process according to the understanding result, plays the corresponding prompt voice to the client and simultaneously returns to the step 2 to wait for the voice instruction of the client;
6) the intelligent voice outbound system work ending condition comprises that a client actively hangs up, changes into manual work, changes into specific service processing and waits overtime.
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