CN111246008A - Method, system and device for realizing telephone assistant - Google Patents
Method, system and device for realizing telephone assistant Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/66—Substation equipment, e.g. for use by subscribers with means for preventing unauthorised or fraudulent calling
- H04M1/663—Preventing unauthorised calls to a telephone set
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
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- G—PHYSICS
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/16—Speech classification or search using artificial neural networks
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
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- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/7243—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality with interactive means for internal management of messages
- H04M1/72436—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality with interactive means for internal management of messages for text messaging, e.g. short messaging services [SMS] or e-mails
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72484—User interfaces specially adapted for cordless or mobile telephones wherein functions are triggered by incoming communication events
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/12—Messaging; Mailboxes; Announcements
- H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2250/00—Details of telephonic subscriber devices
- H04M2250/74—Details of telephonic subscriber devices with voice recognition means
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Abstract
The embodiment of the invention discloses a method, a system and a device for realizing telephone assistant, wherein the embodiment of the invention adopts a trained neural network model to construct a telephone assistant application, an incoming call of a mobile terminal is accessed into the telephone assistant application, the telephone assistant application performs voice recognition and semantic analysis on the content of the incoming call to obtain recognition and analysis information, and after multi-turn pre-conversation is performed on the voice of a user and the incoming call based on the recognition and analysis information, the obtained incoming call intention information is provided for the mobile terminal to be processed. The invention applies the neural network model of deep learning to the incoming call processing process, so that the incoming call can be processed intelligently without the setting of a user.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, a system, and an apparatus for implementing a telephone assistant.
Background
With the development of communication technology, mobile terminals have now penetrated all around into our lives, and great convenience is brought to our lives. Meanwhile, the mobile terminal also brings much trouble to the user, for example, making a harassing call is a channel and means for a merchant to promote sales, and frequently making a call to the user to promote merchandise, and even deceiving the money and the money of the user by making a harassing call.
Currently, there are many technologies like mobile terminal telephone assistants to intercept harassing calls, such as: and downloading and installing security application in the mobile terminal, intercepting certain crank calls, or setting some blacklists in the mobile terminal to achieve the aim of accurate interception. For truly meaningful incoming calls, the telephone assistant allows the user to participate directly. However, the adoption of the security application to identify the crank call sometimes cannot help the user to identify the crank call accurately because of network or updating and other problems; however, the blacklist set in the mobile terminal cannot solve the problem because the telephone number of the crank call is changed frequently. Therefore, the telephone assistant arranged on the mobile terminal cannot bring good experience to the user, and most of the situations are still manually distinguished by the user, so that the time and experience of the user are greatly wasted.
Specifically, the mobile terminal intercepts and processes the crank call in the following ways.
Patent application with patent publication number CN109688276A relates to an incoming call filtering system and method based on artificial intelligence technology, solves the problem of traditional harassment-prevention interception and false interception, and comprises: the call filtering system based on the artificial intelligence technology further comprises a telephone switch, the telephone switch comprises an automatic answering system, and the automatic answering system comprises a number verification module, a voiceprint recognition module, a voice recognition module, a dialogue system module, a voice synthesis module, a dialogue verification module and a storage module. The patent application describes the process of intelligently intercepting harassing calls in detail, but the incoming calls are verified through the preset value of the user, and the conversation with the user needs to be restarted.
Patent application with patent publication number CN109995925A relates to a method, terminal and computer readable storage medium for identifying crank calls, the method includes obtaining identification information of an incoming call when the incoming call is detected, and calculating an incoming call characteristic value of the incoming call according to the identification information and preset identification information; the incoming call is identified according to the incoming call characteristic value and the preset characteristic value, and the problem that the existing identification method of the crank call number cannot accurately and timely identify the crank call number, so that the user experience is not high is solved. It can be seen that the patent application is to use the preset characteristic value and the marking information to carry out harassment interception on the incoming call.
The patent application with the patent publication number of CN106302942A relates to an intelligent method for intercepting crank calls, wherein a voice is preset in an intelligent intercepting system to detect whether an incoming call is a recorded call, comprehensive measures such as strange number secondary connection, white list blacklist, networking inquiry and key monitoring are used for judging and intercepting crank calls, the method can autonomously identify a group dialing incoming call and a recording form incoming call, intelligently network the incoming call number, carry out real-time call monitoring and whole-process recording on the strange incoming call, and carry out voice reminding when a user has key operation, so that recording fraud and group dialing calling can be effectively resisted; the user is protected from the threat of harassment and fraudulent calls. It can be seen that the patent application mainly aims at the scenes of recording fraud, and the recording fraud can be effectively intercepted through presetting the recording.
Patent application with patent publication number CN109672786A relates to a method and device for answering an incoming call, which includes: : step 101, when the terminal receives an incoming call, the voice assistant automatically connects the incoming call; and 103, the voice assistant records the incoming call number and/or the voice content of the incoming call number according to the preset slot position, fills the relevant content into the slot position value corresponding to the preset slot position, and carries out conversation with the incoming call number. The method can realize the function of intelligently processing the incoming call by the voice assistant, the voice assistant can carry out multiple rounds of intelligent conversations with the incoming call number to acquire the incoming call intention and answer the problem of the incoming call number according to the requirement, so that some matters needing emergency processing can be answered to the incoming call user in time, the user is helped to solve the harassing call, the humanization of the intelligent incoming call is improved, and the user experience is improved. It can be seen that the patent application gives all the call right to the voice assistant, and the voice assistant talks with the incoming call on behalf of the user, and finally notifies the user of the content of the conversation.
It can be seen that, when the incoming call is processed to meet the answering requirement of the user, the incoming call can be verified according to the preset information, or the user is prompted after the incoming call is answered by adopting a voice recording telephone or a voice assistant, which requires the user to participate and set before or after the incoming call, and brings inconvenience to the user. Furthermore, the incoming call conversation by adopting the voice recording telephone or the voice assistant is preset corresponding to the corresponding incoming call, and is not intelligent.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method for implementing a telephone assistant, which can process an incoming call intelligently without user setting, so as to meet user requirements.
The embodiment of the invention also provides a system for realizing the telephone assistant, which can intelligently process the incoming call under the condition of not needing the setting of the user so as to meet the requirement of the user.
The embodiment of the invention also provides a device for realizing the telephone assistant, which can intelligently process the incoming call under the condition of not needing the setting of the user so as to meet the requirement of the user.
The embodiment of the invention is realized as follows:
a method for implementing a telephone assistant, the method comprising:
adopting a trained neural network model to construct a telephone assistant application;
accessing an incoming call of a mobile terminal into the telephone assistant application, and performing voice recognition and semantic analysis on the content of the incoming call by the telephone assistant application to obtain recognition analysis information;
the telephone assistant application simulates the user voice to carry out multiple rounds of pre-conversation with the incoming call based on the identification and analysis information, and after the incoming call intention information is obtained, the incoming call intention information is provided for the mobile terminal to be processed.
Before the phone assistant application performs voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information, the method further includes:
setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
The providing the mobile terminal with the processing comprises:
when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form;
and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
The method for constructing the telephone assistant application by adopting the trained neural network model comprises the following steps:
training a neural network model based on an Automatic Speech Recognition (ASR) mode of deep learning and a Natural Language Processing (NLP) mode of deep learning;
the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps:
and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
A system for implementing a telephone assistant, comprising: a mobile terminal, a caller device and an intelligent voice call assistant unit, wherein,
the caller equipment is used for initiating a call to the mobile terminal;
the intelligent voice call assistant unit is used for constructing a telephone assistant application by adopting a trained neural network model, accessing an incoming call of the mobile terminal into the telephone assistant application, and performing voice recognition and semantic analysis on the content of the incoming call by the telephone assistant application to obtain recognition analysis information; after multiple pre-conversations between the voice of the user and the incoming call are simulated based on the recognition analysis information, the incoming call intention information is obtained and provided for the mobile terminal to be processed;
and the mobile terminal is used for carrying out corresponding processing after receiving the incoming call intention information.
The intelligent voice call assistant unit is also used for setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
The mobile terminal is further configured to perform corresponding processing including: when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form; and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
The intelligent voice call assistant unit is also used for constructing the telephone assistant application by adopting the trained neural network model and comprises the following steps: training a neural network model based on an ASR mode of deep learning and an NLP mode of deep learning; the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
An apparatus for implementing a telephone assistant, the apparatus comprising: an intelligent voice answering module, an intelligent voice analysis decision module and an intelligent dialogue subject extraction module, wherein,
the intelligent voice answering module is used for carrying out voice recognition and semantic analysis on an incoming call of the accessed mobile terminal, obtaining recognition analysis information and sending the recognition analysis information to the intelligent voice analysis decision module, and simulating the voice of a user to carry out multiple rounds of pre-conversation with the incoming call under the indication of the intelligent voice analysis decision module;
the intelligent voice analysis decision module is used for making a decision based on the recognition analysis information and indicating the intelligent voice answering module to simulate the voice of a user and carry out multiple rounds of pre-conversation with incoming calls; extracting multi-round pre-conversation contents to make a decision to obtain incoming call intention information;
and the intelligent conversation subject extraction module is used for providing the pre-conversation content to the mobile terminal in a text mode.
The intelligent voice answering module. The system is also used for setting an incoming call intercepting rule, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on incoming call content to obtain recognition analysis information;
the intelligent voice answering module is also used for carrying out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information, and comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
As can be seen from the above, in the embodiments of the present invention, a trained neural network model is used to construct a telephone assistant application, an incoming call of a mobile terminal is accessed to the telephone assistant application, the telephone assistant application performs speech recognition and semantic analysis on the content of the incoming call to obtain recognition analysis information, and after performing multiple rounds of pre-conversation on the incoming call and the speech of a user based on the recognition analysis information, the obtained incoming call intention information is provided to the mobile terminal for processing. The invention applies the neural network model of deep learning to the incoming call processing process, so that the incoming call can be processed intelligently without the setting of a user.
Drawings
Fig. 1 is a schematic process diagram of a method for implementing a telephone assistant according to an embodiment of the present invention;
fig. 2 is a flowchart of an implementation method of a telephone assistant according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an implementation system of a telephone assistant according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus for implementing a telephone assistant according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an implementation of an intelligent voice call assistant unit according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating a natural language processing procedure according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a speech synthesis process provided by an embodiment of the present invention;
FIG. 8 is a schematic diagram of an intelligent speech analysis decision making process according to an embodiment of the present invention;
fig. 9 is a schematic diagram of a basic Recursive NN model according to an embodiment of the present invention;
FIG. 10 is a schematic diagram illustrating slot-based identification provided by embodiments of the present invention;
FIG. 11 is a diagram illustrating an exemplary implementation of a telephone assistant according to an embodiment of the present invention;
fig. 12 is a schematic diagram of a second specific example of implementation of a telephone assistant according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples.
The embodiment of the invention adopts a trained neural network model to construct a telephone assistant application, the incoming call of the mobile terminal is accessed into the telephone assistant application, the telephone assistant application performs voice recognition and semantic analysis on the content of the incoming call to obtain recognition and analysis information, and after multi-turn pre-conversation is performed on the voice of a user and the incoming call is simulated based on the recognition and analysis information, the incoming call intention information is obtained and provided for the mobile terminal to process.
In this way, the invention applies the deep learning neural network model to the incoming call processing process, so that the incoming call can be intelligently processed without the setting of a user.
The telephone assistant application provided by the embodiment of the invention can simulate the voice of a user to carry out multiple rounds of pre-conversation with the telephone before the user answers the telephone, identify the incoming call intention information through a deep learning technology, intelligently judge whether to continue answering according to the incoming call intention information, and send an information notification after hanging up to inform the incoming call intention and the reason of hanging up if not to continue answering; when the user of the mobile terminal is required to answer the call, the mobile terminal pops up a window whether to answer the call normally, and the pre-conversation content is displayed in the pop-up window of the mobile terminal in a text form, so that the user can conveniently and seamlessly communicate with the caller. The whole implementation process is schematically shown in fig. 1.
Specifically, when the mobile terminal receives an incoming call, the mobile terminal accesses the incoming call to the set telephone assistant application, a black list and a white list can be set in the telephone assistant application, and the telephone assistant application preprocesses the incoming call according to the set black list and the set white list: if the incoming call number is in the blacklist, the incoming call is hung up directly, and if the incoming call number is in the white list, the incoming call is connected directly to the mobile terminal; if the incoming call number is not in the black list or the white list, the telephone assistant application performs voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information, and simulates the user voice and the incoming call to perform multiple rounds of pre-conversation based on the recognition analysis information to obtain the incoming call intention information. The telephone assistant application confirms that the incoming call is a harassing call or an incoming call within a preset threshold value according to the incoming call intention information, and the incoming call is directly hung up and simultaneously informed to the mobile terminal in a short message form; the telephone assistant application confirms that the incoming call is a normal incoming call according to the incoming call intention information, the incoming call is handed to the mobile terminal to be directly answered, and meanwhile, the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form, so that a user can know the purpose of the incoming call in advance, and the user can communicate with the caller more effectively.
In the embodiment of the present invention, the phone assistant application may be called an intelligent voice call assistant, and may be disposed in a switch provided by a telecommunications carrier, where the switch is disposed between the mobile terminal and a caller device to process an incoming call.
Therefore, after the mobile terminal uses the set telephone assistant application, the incoming call can be efficiently processed according to the intention of the user main body, the incoming call which is not interested by the user is directly hung up, the incoming call which is interested by the user is answered by the user, and the pre-talking content can be displayed on the user interaction interface of the mobile terminal in a text form before answering, so that the user can know the purpose of the incoming call in advance and make a more appropriate arrangement reply.
Fig. 2 is a flowchart of an implementation method of a telephone assistant according to an embodiment of the present invention, which includes the following specific steps:
and 203, simulating the user voice and the incoming call to carry out multiple pre-conversations by the telephone assistant application based on the identification and analysis information, obtaining incoming call intention information, and providing the incoming call intention information for the mobile terminal to process.
In the method, before the phone assistant application performs speech recognition and semantic analysis on the incoming call content to obtain recognition analysis information, the method further includes:
setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
Here, the incoming call interception rule is a set call interception threshold or a priority call threshold, or a black list and a white list set for the user identifier, and performs a direct pre-filtering operation.
In the method, the providing for the mobile terminal comprises:
when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form;
and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
In the method, the building of the telephone assistant application by using the trained neural network model comprises the following steps:
training a neural network model based on an Automatic Speech Recognition (ASR) mode of deep learning and a Natural Language Processing (NLP) mode of deep learning;
the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps:
and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
Fig. 3 is a schematic structural diagram of an implementation system of a telephone assistant according to an embodiment of the present invention, including: a mobile terminal, a caller device and an intelligent voice call assistant unit, wherein,
the caller equipment is used for initiating a call to the mobile terminal;
the intelligent voice call assistant unit is used for constructing a telephone assistant application by adopting a trained neural network model, accessing an incoming call of the mobile terminal into the telephone assistant application, and performing voice recognition and semantic analysis on the content of the incoming call by the telephone assistant application to obtain recognition analysis information; after multiple pre-conversations between the voice of the user and the incoming call are simulated based on the recognition analysis information, the incoming call intention information is obtained and provided for the mobile terminal to be processed;
and the mobile terminal is used for carrying out corresponding processing after receiving the incoming call intention information.
In the system, the intelligent voice call assistant unit is also used for setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
In this system, the mobile terminal is further configured to perform corresponding processing including: when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form; and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
In the system, the intelligent voice call assistant unit is further configured to construct a telephone assistant application by using the trained neural network model, and the method includes: training a neural network model based on an ASR mode of deep learning and an NLP mode of deep learning; the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
In this system, the intelligent voice call assistant unit may be provided in an exchange provided by a telecommunications operator.
Fig. 4 is a schematic structural diagram of an implementation apparatus of a telephone assistant according to an embodiment of the present invention, where the apparatus is an intelligent voice call assistant unit, and includes: an intelligent voice answering module, an intelligent voice analysis decision module and an intelligent dialogue subject extraction module, wherein,
the intelligent voice answering module is used for carrying out voice recognition and semantic analysis on an incoming call of the accessed mobile terminal, obtaining recognition analysis information and sending the recognition analysis information to the intelligent voice analysis decision module, and simulating the voice of a user to carry out multiple rounds of pre-conversation with the incoming call under the indication of the intelligent voice analysis decision module;
the intelligent voice analysis decision module is used for making a decision based on the recognition analysis information and indicating the intelligent voice answering module to simulate the voice of a user and carry out multiple rounds of pre-conversation with incoming calls; extracting multi-round pre-conversation contents to make a decision to obtain incoming call intention information;
and the intelligent conversation subject extraction module is used for providing the pre-conversation content to the mobile terminal in a text mode.
In the device, the intelligent voice answering module is also used for setting an incoming call intercepting rule, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
In the device, the intelligent voice answering module is further used for performing voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
Fig. 5 is a schematic diagram illustrating an implementation of an intelligent voice call assistant unit according to an embodiment of the present invention. As shown in the figure, specifically, the intelligent voice answering module in the intelligent voice call assistant unit includes three parts: speech recognition, semantic analysis, speech synthesis. After the incoming call number passes the number verification, the voice recognition is firstly carried out, and the form of converting the voice into the text can be realized based on the ASR technology of deep learning. And then, entering an NLP mode of deep learning, performing natural speech understanding (NLU) and Natural Language Generation (NLG) processing on the text, and inferring incoming call intention information. And meanwhile, the obtained intention text is transmitted to an intelligent voice analysis decision-making module, and the voice analysis decision-making module carries out the next operation.
When the intelligent voice analysis decision module makes a decision and needs to have a conversation with the incoming call, the reply text is sent to the intelligent voice answering module, the reply text is converted into reply voice by the voice synthesis technology, the voice synthesis technology is mature, different voices can be selected to reply according to own preferences, and the voice can be recorded by the caller, so that the caller can feel that the caller is in communication with the caller.
FIG. 6 is a diagram illustrating a natural language processing procedure according to an embodiment of the present invention; fig. 7 is a schematic diagram of a speech synthesis process according to an embodiment of the present invention, in which the processes shown in fig. 6 and fig. 7 are applied.
The intelligent voice analysis decision module provided by the embodiment of the invention performs text analysis according to the intention text transmitted by the intelligent voice answer module, and if the answer is a general statement, the intelligent telephone assistant can autonomously generate a reply text and send the reply text to the intelligent voice answer module; if the sentence is in the user threshold range, the intelligent telephone assistant can be directly hung up and informs the mobile terminal in a short message form; if the call is normal after analysis and the mobile terminal needs to be put through by itself, the call request is sent to the mobile terminal, and the communication text is displayed on the call user interface in the mobile terminal, so that the effect of seamless conversation between the user and the caller is achieved. As shown in fig. 8, fig. 8 is a schematic diagram of an intelligent speech analysis decision process according to an embodiment of the present invention.
According to the intelligent dialogue gist extraction module provided by the embodiment of the invention, when a user of the mobile terminal needs to answer the phone personally, the intelligent voice dialogue module sends the dialogue text between the caller and the caller to the intelligent dialogue gist extraction module. The intelligent voice conversation theme extraction module can obtain the theme of the conversation text by passing through a plurality of combined models based on the existing large data set. Here, RecNN + Viterbi is taken as an example for explanation, as shown in fig. 9 and fig. 10, fig. 9 is a schematic diagram of a basic Recursive NN model provided in the embodiment of the present invention, and fig. 10 is a schematic diagram of slot-based identification provided in the embodiment of the present invention.
The incoming call input is a single word vector (the subsequent optimization input is a word vector of a window), each part of speech is regarded as a weight vector (weight vector), and thus the operation of each word on the path is a simple dot product operation of the word vector and the part of speech weight vector. The square in the figure is the result of the dot product operation of the part-of-speech weight vector and the input vector. When a parent node has multiple child branches, it can be considered that each branch is summed with a weighted dot product. For example, the word "IN" indicates that the path IN the semantic analysis tree is "IN-PP-NP", each output vector of the path is subjected to a weighted operation to obtain the path feature, and the concat of the path feature of the three words is used as the tri-path feature to classify the slots, so that the prediction of the "IN" is performed.
The following three specific examples are provided to illustrate the embodiments of the present invention in detail
Example one: advertisement promotion telephone interception
As shown in fig. 11, fig. 11 is a schematic diagram of a specific example of implementation of a telephone assistant according to an embodiment of the present invention, including:
the first step, the telephone assistant application receives the incoming call, and firstly enters an intelligent voice answering module;
secondly, in the intelligent voice answering module, after being recognized by ASR, the intelligent voice answering module enters an NLU module, and words and sentences of the sentence are analyzed to understand the semantics of the sentence;
step three, entering an NLG module, and translating a corresponding keyword text 'real estate' aiming at the analyzed semantics;
step four, the intelligent voice answering module sends the obtained intention text 'real estate' to the intelligent voice analysis decision module;
step five, an intelligent voice analysis decision module is used for obtaining the fact that the user wants to filter out the related incoming call of the 'house property' according to the previous habit of the user;
sixthly, the intelligent voice analysis decision module sends the reply text 'thank you, no need' to the intelligent voice answering module;
seventhly, the intelligent voice answering module synthesizes the user voice and incoming call dialogue through a voice synthesis technology, wherein the answer text is 'thank you, not needed';
and step eight, the intelligent voice analysis decision module hangs up the phone and sends information to the mobile terminal used by the user.
Example two: telephone through of friend
As shown in fig. 12, fig. 12 is a schematic diagram of a second specific example of implementation of a telephone assistant according to an embodiment of the present invention, including:
the first step, the telephone assistant application receives the incoming call, and firstly enters an intelligent voice answering module;
secondly, after the intelligent voice answer module is identified by ASR, the intelligent voice answer module enters an NLU module to analyze words and sentences of the sentence and understand the semantics of the sentence;
step three, entering an NLG module, and translating corresponding keyword texts 'small bright, and empty today' according to the analyzed semantics;
step four, the intelligent voice answering module sends the obtained intention text 'bright and available today' to the intelligent voice analysis decision module;
a fifth step, an intelligent voice analysis decision-making module, which is obtained according to a large amount of previous training, wherein the text is a common greeting phrase;
step six, the intelligent voice analysis decision module autonomously replies and sends a reply text 'do things exist' to the intelligent voice answer module;
step seven, the intelligent voice answering module synthesizes the user voice and incoming call dialogue according to the reply text 'do there is something';
eighth step, the caller initiates a second round of communication, "i go on business in Nanjing, go to school at night and find out xiaowei and wins together and drink two cups";
a ninth step of extracting an intention text 'find a little great at night, near school and win drinking' by an intelligent voice answer module;
a tenth step, analyzing the question-answer phrases by an intelligent voice analysis decision module, and requiring the user to answer the question-answer phrases autonomously;
step eleven, the intelligent voice analysis decision module sends the dialogue text 'little bright, available today, and in the evening, little great, cheerful and drinking' to the intelligent dialogue idea extraction module;
a twelfth step, an intelligent dialogue idea extraction module, which is used for obtaining idea ideas through a deep learning model according to the pre-communicated intention texts;
thirteenth step, the intelligent voice analysis decision module transfers the call to the mobile terminal and displays the idea, and the user of the mobile terminal can know the intention of the incoming call in advance, make a pre-judgment and carry out seamless communication with the incoming call.
Example three: recording active phone reminders according to memos
The specific process of this example is:
the first step, the telephone assistant application knows that friday users and friends are supposed to eat together according to the user memo;
a second step, on thursday, the user has not called something to eat with the xiao liang;
step three, the telephone assistant actively broadcasts the telephone of the user to remind the user of the fact that the user eats in friday when the telephone assistant is applied to the thursday;
the fourth step, the telephone assistant application consults whether the user needs to talk with the little light;
and fifthly, when the user agrees to talk, the telephone assistant application actively dials the small bright telephone and appoints to eat.
Therefore, the voice assistant application provided by the embodiment of the invention obtains the corresponding keyword text according to the voice recognition of the incoming call and the NLP technology, compares the keyword text with the existing text threshold in the database, achieves the purposes of filtering advertisement promotion and user-defined interception, and can help the user to pre-communicate the incoming call before answering the normal incoming call, thereby facilitating the more effective conversation of the user. The intelligent telephone assistant greatly facilitates users and improves user experience.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for implementing a telephone assistant, the method comprising:
adopting a trained neural network model to construct a telephone assistant application;
accessing an incoming call of a mobile terminal into the telephone assistant application, and performing voice recognition and semantic analysis on the content of the incoming call by the telephone assistant application to obtain recognition analysis information;
the telephone assistant application simulates the user voice to carry out multiple rounds of pre-conversation with the incoming call based on the identification and analysis information, and after the incoming call intention information is obtained, the incoming call intention information is provided for the mobile terminal to be processed.
2. The method of claim 1, wherein before the phone assistant application performs speech recognition and semantic analysis on the incoming call content to obtain recognition analysis information, the method further comprises:
setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
3. The method of claim 1, wherein said providing the mobile terminal with processing comprises:
when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form;
and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
4. The method of claim 1, wherein the building the telephony assistant application using the trained neural network model comprises:
training a neural network model based on an Automatic Speech Recognition (ASR) mode of deep learning and a Natural Language Processing (NLP) mode of deep learning;
the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps:
and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
5. A system for implementing a telephone assistant, comprising: a mobile terminal, a caller device and an intelligent voice call assistant unit, wherein,
the caller equipment is used for initiating a call to the mobile terminal;
the intelligent voice call assistant unit is used for constructing a telephone assistant application by adopting a trained neural network model, accessing an incoming call of the mobile terminal into the telephone assistant application, and performing voice recognition and semantic analysis on the content of the incoming call by the telephone assistant application to obtain recognition analysis information; after multiple pre-conversations between the voice of the user and the incoming call are simulated based on the recognition analysis information, the incoming call intention information is obtained and provided for the mobile terminal to be processed;
and the mobile terminal is used for carrying out corresponding processing after receiving the incoming call intention information.
6. The apparatus of claim 5,
the intelligent voice call assistant unit is also used for setting an incoming call intercepting rule in the telephone assistant application, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; and if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information.
7. The apparatus of claim 6,
the mobile terminal is further configured to perform corresponding processing including: when the incoming call is confirmed to be a harassing call or a call within a preset threshold value according to the incoming call intention information, the incoming call is directly hung up and is notified to the mobile terminal in a short message form; and when the incoming call is confirmed to be a normal incoming call according to the incoming call intention information, the mobile terminal answers directly, and simultaneously the pre-conversation content is displayed on a user interaction interface of the mobile terminal in a text form.
8. The apparatus of claim 6, wherein the intelligent voice call assistant unit, further configured to build a telephony assistant application using the trained neural network model, comprises: training a neural network model based on an ASR mode of deep learning and an NLP mode of deep learning; the telephone assistant application performs voice recognition and semantic analysis on incoming call content to obtain recognition analysis information, and the recognition analysis information comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
9. An apparatus for implementing a telephone assistant, the apparatus comprising: an intelligent voice answering module, an intelligent voice analysis decision module and an intelligent dialogue subject extraction module, wherein,
the intelligent voice answering module is used for carrying out voice recognition and semantic analysis on an incoming call of the accessed mobile terminal, obtaining recognition analysis information and sending the recognition analysis information to the intelligent voice analysis decision module, and simulating the voice of a user to carry out multiple rounds of pre-conversation with the incoming call under the indication of the intelligent voice analysis decision module;
the intelligent voice analysis decision module is used for making a decision based on the recognition analysis information and indicating the intelligent voice answering module to simulate the voice of a user and carry out multiple rounds of pre-conversation with incoming calls; extracting multi-round pre-conversation contents to make a decision to obtain incoming call intention information;
and the intelligent conversation subject extraction module is used for providing the pre-conversation content to the mobile terminal in a text mode.
10. The apparatus of claim 9, wherein the intelligent voice response module. The system is also used for setting an incoming call intercepting rule, pre-filtering an incoming call according to the incoming call intercepting rule, and directly intercepting the incoming call if the incoming call intercepting rule is met; if the incoming call interception rule is not met, directly connecting the incoming call to the mobile terminal; if the incoming call interception rule can not be determined to be met, executing the step that the telephone assistant application carries out voice recognition and semantic analysis on incoming call content to obtain recognition analysis information;
the intelligent voice answering module is also used for carrying out voice recognition and semantic analysis on the incoming call content to obtain recognition analysis information, and comprises the following steps: and after the incoming call of the mobile terminal is converted from voice to text in an ASR mode, language processing is carried out in an NLP mode to obtain analysis information.
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