CN113111759A - Customer confirmation detection method and device in double-record data quality inspection - Google Patents
Customer confirmation detection method and device in double-record data quality inspection Download PDFInfo
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Abstract
The invention provides a customer confirmation detection method and a customer confirmation detection device in double-record data quality inspection, which can be used in the financial field or other fields. The method comprises the following steps: acquiring double-recording data, and decomposing the double-recording data into video data and audio data; performing confirmation action detection on the video data to obtain a confirmation action detection result; performing voice recognition on the audio data to obtain voice text data, and performing text rule matching on the voice text data to obtain a text matching result; and generating a customer confirmation detection result according to the confirmation action detection result and the text matching result. According to the invention, the detection accuracy of the customer confirmation link in the double-record quality detection is improved by identifying and detecting the video data and the audio data, and meanwhile, the identification and detection are carried out by utilizing the confirmation action of the customer, so that the problem of low detection accuracy caused by the fact that the detection is carried out only by converting voice into text is solved, and the detection success rate of the double-record quality detection is further improved.
Description
Technical Field
The invention relates to the technical field of audio and video processing, in particular to a client confirmation detection method and device in double-record data quality inspection.
Background
In order to protect the rights and interests of consumers, the supervision and administration organization requires the commercial banking industry and financial institutions to standardize the sales behaviors of the financial institutions through sound recording and video recording (double recording) when the financial products such as financing and insurance policy are sold. At present, commercial banks usually adopt local cache video files, and asynchronously upload the video files to a cloud for storage after the whole double-recording video is recorded, so as to be ready for compliance examination by subsequent supervision departments.
In order to ensure the compliance of the double-recording video, the financial institution generally adopts an artificial intelligence technology to check the offline audio/video data, but has the problem that the accurate detection cannot be carried out on the link of customer confirmation, so that the success rate of quality inspection is not high. The customer confirmation link depends on rule matching after the voice is converted into the text, but when the speaking voice of the customer is small or the environment is noisy, the quality inspection is easily failed in the customer confirmation link.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiments of the present invention mainly aim to provide a method and an apparatus for detecting customer confirmation in quality inspection of double-record data, so as to realize accurate detection of a customer confirmation link.
In order to achieve the above object, an embodiment of the present invention provides a method for detecting customer confirmation in quality inspection of double-record data, where the method includes:
acquiring double-recording data, and decomposing the double-recording data into video data and audio data;
performing confirmation action detection on the video data to obtain a confirmation action detection result;
performing voice recognition on the audio data to obtain voice text data, and performing text rule matching on the voice text data to obtain a text matching result;
and generating a customer confirmation detection result according to the confirmation action detection result and the text matching result.
Optionally, in an embodiment of the present invention, the performing the confirmation action detection on the video data to obtain a result of the confirmation action detection includes:
performing nodding detection, gesture detection and lip language detection on the video data to respectively obtain a nodding detection result, a gesture detection result and a lip language detection result;
and determining whether the confirmation action detection result passes the detection according to the nodding detection result, the gesture detection result and the lip language detection result, and if any one of the nodding detection result, the gesture detection result and the lip language detection result passes the detection, determining that the confirmation action detection result passes the detection.
Optionally, in an embodiment of the present invention, the performing text rule matching on the voice text data to obtain a text matching result includes:
and determining whether the voice text data accords with the matching rule according to a preset matching rule, wherein if the voice text data accords with the matching rule, the text matching result is that the matching is passed.
Optionally, in an embodiment of the present invention, the generating a customer confirmation detection result according to the confirmation action detection result and the text matching result includes:
and determining whether the detection result of the confirmation action is passed or not, or whether the text matching result is passed or not, and if the detection result of the confirmation action is passed or the text matching result is passed, determining that the generated detection result of the client is passed.
The embodiment of the invention also provides a client confirmation detection device in the quality inspection of double-record data, which comprises:
the data acquisition module is used for acquiring double-recording data and decomposing the double-recording data into video data and audio data;
the action detection module is used for carrying out confirmation action detection on the video data to obtain a confirmation action detection result;
the rule matching module is used for carrying out voice recognition on the audio data to obtain voice text data and carrying out text rule matching on the voice text data to obtain a text matching result;
and the detection result module is used for generating a client confirmation detection result according to the confirmation action detection result and the text matching result.
Optionally, in an embodiment of the present invention, the action detection module includes:
the motion detection unit is used for performing nodding detection, gesture detection and lip language detection on the video data to respectively obtain a nodding detection result, a gesture detection result and a lip language detection result;
and the detection result unit is used for determining whether the confirmation action detection result passes the detection according to the nodding detection result, the gesture detection result and the lip language detection result, and if any one of the nodding detection result, the gesture detection result and the lip language detection result passes the detection, the confirmation action detection result passes the detection.
Optionally, in an embodiment of the present invention, the rule matching module is further configured to determine whether the voice text data meets the matching rule according to a preset matching rule, and if the voice text data meets the matching rule, the text matching result is that the matching is passed.
Optionally, in an embodiment of the present invention, the detection result module is further configured to determine whether the detection result of the confirmation action is a pass detection result or whether the text matching result is a pass matching result, and if the detection result of the confirmation action is a pass detection result or the text matching result is a pass matching result, the generated customer confirms that the detection result is a pass.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
According to the invention, the detection accuracy of the customer confirmation link in the double-record quality detection is improved by identifying and detecting the video data and the audio data, and meanwhile, the identification and detection are carried out by utilizing the confirmation action of the customer, so that the problem of low detection accuracy caused by the fact that the detection is carried out only by converting voice into text is solved, and the detection success rate of the double-record quality detection is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a customer confirmation detection method in a double-record data quality inspection according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating the method of obtaining a confirmation action detection result according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a customer confirmation detection apparatus in a double-record data quality inspection according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an operation detection module according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method and a device for confirming and detecting a client in double-record data quality inspection, which can be used in the financial field or other fields.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart illustrating a method for detecting customer confirmation in a double-record data quality inspection according to an embodiment of the present invention, where an implementation subject of the method for detecting customer confirmation in a double-record data quality inspection according to an embodiment of the present invention includes, but is not limited to, a computer. The method shown in the figure comprises the following steps:
step S1, acquiring the double-recording data, and decomposing the double-recording data into video data and audio data.
The method comprises the steps of acquiring double recording (video recording and audio recording) data through video recording and audio recording equipment, and separating the acquired double recording data. Specifically, the FFMPEG tool may be used to separate the double-recorded data to obtain the video data and the audio data.
Step S2, performing a confirmation operation detection on the video data to obtain a confirmation operation detection result.
The video data confirmation action detection is to identify and detect the video data and judge whether the customer in the video data has a confirmation action.
Specifically, the video data is subjected to nodding detection, whether the nodding action occurs in the client is judged, and the nodding detection can be realized by adopting a head posture estimation algorithm such as Hopenet. And if the head nodding action of the client is detected, the head nodding detection result is that the detection is passed, otherwise, the head nodding detection result is that the detection is not passed.
Further, gesture detection is performed on the video data, whether a gesture confirmation action, such as a gesture of OK, occurs to the client is determined, and gesture recognition can be performed by using an existing gesture recognition technology, such as a Baidu AI open platform. And if the gesture confirmation action of the client is detected, the gesture detection result is that the detection is passed, otherwise, the gesture detection result is that the gesture detection result is not passed.
Further, lip language detection is performed on the video data, whether the client speaks an affirmative feed for agreeing, understanding, knowing or understanding or the like is judged, and lip language detection can be performed by adopting a coupled 3D convolutional neural network. And if the fact that the client speaks the positive feed is detected, the lip language detection result is that the detection is passed, and otherwise, the lip language detection result is that the detection is not passed.
Further, when any one of the nodding detection result, the gesture detection result and the lip language detection result is passed, indicating that the client expresses positive feedback, generating a confirmation action detection result, and confirming that the action detection result is passed. And if the nodding detection result, the gesture detection result and the lip language detection result are all failed, generating a confirmed action detection result, and confirming that the action detection result is failed.
And step S3, performing voice recognition on the audio data to obtain voice text data, and performing text rule matching on the voice text data to obtain a text matching result.
The voice recognition technology can be adopted to perform voice recognition on the audio data to obtain voice text data. In addition, text rule matching is carried out on the voice text data through a preset matching rule.
Specifically, the preset matching rule includes positive feedback information, for example, the positive feedback information is possible words of agreement, understanding, and the like. And matching the text rules of the voice text data, wherein if the voice text data comprises positive feedback information in the matching rules, the client expresses clear confirmation feedback, and the text matching result is that the matching is passed. If the voice text data does not include the positive feedback information in the matching rule, the client does not express the confirmation feedback, and the text matching result is failed.
Further, the preset matching rule further includes a service problem corresponding to the positive feedback information, for example, the positive feedback information should follow the corresponding specific service problem. When the text rule matching is performed on the voice text data, the positive feedback information can be determined to be a response aiming at the service problem by combining the service problem corresponding to the positive feedback information. For example, the service question is to ask whether the client knows the attention of service handling, and the client gives the positive feedback information "know" after the service question, thereby determining that the client expresses clear confirmation feedback and the text matching result is that the matching is passed.
And step S4, generating a client confirmation detection result according to the confirmation action detection result and the text matching result.
If the action detection result is confirmed to be passed or the text matching result is matched to be passed, the client expresses clear confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is passed. And if the confirmation action detection result and the text matching result are both failed, the client does not express confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is failed.
As an embodiment of the present invention, as shown in fig. 2, performing a confirmation action detection on the video data, and obtaining a confirmation action detection result includes:
step S21, performing nodding detection, gesture detection and lip language detection on the video data to respectively obtain a nodding detection result, a gesture detection result and a lip language detection result.
Step S22, determining whether the confirmation action detection result passes the detection according to the nodding detection result, the gesture detection result, and the lip language detection result, and if any one of the nodding detection result, the gesture detection result, and the lip language detection result passes the detection, determining that the confirmation action detection result passes the detection.
The video data is subjected to nodding detection, whether nodding action occurs in a client or not is judged, and the nodding action can be realized by adopting a head posture estimation algorithm such as Hopenet and the like. And if the head nodding action of the client is detected, the head nodding detection result is that the detection is passed, otherwise, the head nodding detection result is that the detection is not passed.
Further, gesture detection is performed on the video data, whether a gesture confirmation action, such as a gesture of OK, occurs to the client is determined, and gesture recognition can be performed by using an existing gesture recognition technology, such as a Baidu AI open platform. And if the gesture confirmation action of the client is detected, the gesture detection result is that the detection is passed, otherwise, the gesture detection result is that the gesture detection result is not passed.
Further, lip language detection is performed on the video data, whether the client speaks an affirmative feed for agreeing, understanding, knowing or understanding or the like is judged, and lip language detection can be performed by adopting a coupled 3D convolutional neural network. And if the fact that the client speaks the positive feed is detected, the lip language detection result is that the detection is passed, and otherwise, the lip language detection result is that the detection is not passed.
Further, when any one of the nodding detection result, the gesture detection result and the lip language detection result is passed, indicating that the client expresses positive feedback, generating a confirmation action detection result, and confirming that the action detection result is passed. And if the nodding detection result, the gesture detection result and the lip language detection result are all failed, generating a confirmed action detection result, and confirming that the action detection result is failed.
As an embodiment of the present invention, performing text rule matching on the voice text data to obtain a text matching result includes: and determining whether the voice text data accords with the matching rule according to a preset matching rule, wherein if the voice text data accords with the matching rule, the text matching result is that the matching is passed.
The preset matching rule includes positive feedback information, for example, the positive feedback information is possible words such as agreement, understanding and the like. And matching the text rules of the voice text data, wherein if the voice text data comprises positive feedback information in the matching rules, the client expresses clear confirmation feedback, and the text matching result is that the matching is passed. If the voice text data does not include the positive feedback information in the matching rule, the client does not express the confirmation feedback, and the text matching result is failed.
Further, the preset matching rule further includes a service problem corresponding to the positive feedback information, for example, the positive feedback information should follow the corresponding specific service problem. When the text rule matching is performed on the voice text data, the positive feedback information can be determined to be a response aiming at the service problem by combining the service problem corresponding to the positive feedback information. For example, the service question is to ask whether the client knows the attention of service handling, and the client gives the positive feedback information "know" after the service question, thereby determining that the client expresses clear confirmation feedback and the text matching result is that the matching is passed.
As an embodiment of the present invention, generating a customer confirmation detection result according to the confirmation action detection result and the text matching result includes: and determining whether the detection result of the confirmation action is passed or not, or whether the text matching result is passed or not, and if the detection result of the confirmation action is passed or the text matching result is passed, determining that the generated detection result of the client is passed.
If the action detection result is confirmed to be passed or the text matching result is matched to be passed, the client expresses clear confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is passed. And if the confirmation action detection result and the text matching result are both failed, the client does not express confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is failed.
According to the invention, the detection accuracy of the customer confirmation link in the double-record quality detection is improved by identifying and detecting the video data and the audio data, and meanwhile, the identification and detection are carried out by utilizing the confirmation action of the customer, so that the problem of low detection accuracy caused by the fact that the detection is carried out only by converting voice into text is solved, and the detection success rate of the double-record quality detection is further improved.
Fig. 3 is a schematic structural diagram of a customer confirmation detection apparatus in a double-record data quality inspection according to an embodiment of the present invention, where the apparatus includes:
the data acquiring module 10 is configured to acquire double-recording data and decompose the double-recording data into video data and audio data.
The method comprises the steps of acquiring double recording (video recording and audio recording) data through video recording and audio recording equipment, and separating the acquired double recording data. Specifically, the FFMPEG tool may be used to separate the double-recorded data to obtain the video data and the audio data.
And the action detection module 20 is configured to perform confirmation action detection on the video data to obtain a confirmation action detection result.
The video data confirmation action detection is to identify and detect the video data and judge whether the customer in the video data has a confirmation action.
Specifically, the video data is subjected to nodding detection, whether the nodding action occurs in the client is judged, and the nodding detection can be realized by adopting a head posture estimation algorithm such as Hopenet. And if the head nodding action of the client is detected, the head nodding detection result is that the detection is passed, otherwise, the head nodding detection result is that the detection is not passed.
Further, gesture detection is performed on the video data, whether a gesture confirmation action, such as a gesture of OK, occurs to the client is determined, and gesture recognition can be performed by using an existing gesture recognition technology, such as a Baidu AI open platform. And if the gesture confirmation action of the client is detected, the gesture detection result is that the detection is passed, otherwise, the gesture detection result is that the gesture detection result is not passed.
Further, lip language detection is performed on the video data, whether the client speaks an affirmative feed for agreeing, understanding, knowing or understanding or the like is judged, and lip language detection can be performed by adopting a coupled 3D convolutional neural network. And if the fact that the client speaks the positive feed is detected, the lip language detection result is that the detection is passed, and otherwise, the lip language detection result is that the detection is not passed.
Further, when any one of the nodding detection result, the gesture detection result and the lip language detection result is passed, indicating that the client expresses positive feedback, generating a confirmation action detection result, and confirming that the action detection result is passed. And if the nodding detection result, the gesture detection result and the lip language detection result are all failed, generating a confirmed action detection result, and confirming that the action detection result is failed.
And the rule matching module 30 is configured to perform voice recognition on the audio data to obtain voice text data, and perform text rule matching on the voice text data to obtain a text matching result.
The voice recognition technology can be adopted to perform voice recognition on the audio data to obtain voice text data. In addition, text rule matching is carried out on the voice text data through a preset matching rule.
Specifically, the preset matching rule includes positive feedback information, for example, the positive feedback information is possible words of agreement, understanding, and the like. And matching the text rules of the voice text data, wherein if the voice text data comprises positive feedback information in the matching rules, the client expresses clear confirmation feedback, and the text matching result is that the matching is passed. If the voice text data does not include the positive feedback information in the matching rule, the client does not express the confirmation feedback, and the text matching result is failed.
Further, the preset matching rule further includes a service problem corresponding to the positive feedback information, for example, the positive feedback information should follow the corresponding specific service problem. When the text rule matching is performed on the voice text data, the positive feedback information can be determined to be a response aiming at the service problem by combining the service problem corresponding to the positive feedback information. For example, the service question is to ask whether the client knows the attention of service handling, and the client gives the positive feedback information "know" after the service question, thereby determining that the client expresses clear confirmation feedback and the text matching result is that the matching is passed.
And the detection result module 40 is used for generating a client confirmation detection result according to the confirmation action detection result and the text matching result.
If the action detection result is confirmed to be passed or the text matching result is matched to be passed, the client expresses clear confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is passed. And if the confirmation action detection result and the text matching result are both failed, the client does not express confirmation feedback, a client confirmation detection result is generated, and the client confirms that the detection result is failed.
As an embodiment of the present invention, as shown in fig. 4, the motion detection module 20 includes:
the action detection unit 21 is configured to perform nodding detection, gesture detection and lip language detection on the video data to obtain a nodding detection result, a gesture detection result and a lip language detection result, respectively;
a detection result unit 22, configured to determine whether the confirmation action detection result passes detection according to the nodding detection result, the gesture detection result, and the lip language detection result, and if any one of the nodding detection result, the gesture detection result, and the lip language detection result passes detection, determine that the confirmation action detection result passes detection.
As an embodiment of the present invention, the rule matching module is further configured to determine whether the voice text data conforms to the matching rule according to a preset matching rule, and if the voice text data conforms to the matching rule, the text matching result is that matching is passed.
As an embodiment of the present invention, the detection result module is further configured to determine whether the detection result of the confirmation action is a pass detection result or whether the text matching result is a pass matching result, and if the detection result of the confirmation action is a pass detection result or the text matching result is a pass matching result, the generated customer confirmation detection result is a pass.
Based on the same application concept as the customer confirmation detection method in the double-record data quality inspection, the invention also provides a customer confirmation detection device in the double-record data quality inspection. The principle of solving the problems of the client confirmation detection device in the double-record data quality inspection is similar to that of a client confirmation detection method in the double-record data quality inspection, so that the implementation of the client confirmation detection device in the double-record data quality inspection can refer to the implementation of the client confirmation detection method in the double-record data quality inspection, and repeated parts are not repeated.
According to the invention, the detection accuracy of the customer confirmation link in the double-record quality detection is improved by identifying and detecting the video data and the audio data, and meanwhile, the identification and detection are carried out by utilizing the confirmation action of the customer, so that the problem of low detection accuracy caused by the fact that the detection is carried out only by converting voice into text is solved, and the detection success rate of the double-record quality detection is further improved.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
As shown in fig. 5, the electronic device 600 may further include: communication module 110, input unit 120, audio processing unit 130, display 160, power supply 170. It is noted that the electronic device 600 does not necessarily include all of the components shown in fig. 5; furthermore, the electronic device 600 may also comprise components not shown in fig. 5, which may be referred to in the prior art.
As shown in fig. 5, the central processor 100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, the central processor 100 receiving input and controlling the operation of the various components of the electronic device 600.
The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 100 may execute the program stored in the memory 140 to realize information storage or processing, etc.
The input unit 120 provides input to the cpu 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display an object to be displayed, such as an image or a character. The display may be, for example, an LCD display, but is not limited thereto.
The memory 140 may be a solid state memory such as Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 140 may also be some other type of device. Memory 140 includes buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage section 142, and the application/function storage section 142 is used to store application programs and function programs or a flow for executing the operation of the electronic device 600 by the central processing unit 100.
The memory 140 may also include a data store 143, the data store 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage portion 144 of the memory 140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging application, address book application, etc.).
The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter/receiver) 110 is coupled to the central processor 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132 to implement general telecommunications functions. Audio processor 130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, an audio processor 130 is also coupled to the central processor 100, so that recording on the local can be enabled through a microphone 132, and so that sound stored on the local can be played through a speaker 131.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method for customer confirmation detection in double-record data quality inspection, the method comprising:
acquiring double-recording data, and decomposing the double-recording data into video data and audio data;
performing confirmation action detection on the video data to obtain a confirmation action detection result;
performing voice recognition on the audio data to obtain voice text data, and performing text rule matching on the voice text data to obtain a text matching result;
and generating a customer confirmation detection result according to the confirmation action detection result and the text matching result.
2. The method of claim 1, wherein the performing a confirmation action detection on the video data and obtaining a confirmation action detection result comprises:
performing nodding detection, gesture detection and lip language detection on the video data to respectively obtain a nodding detection result, a gesture detection result and a lip language detection result;
and determining whether the confirmation action detection result passes the detection according to the nodding detection result, the gesture detection result and the lip language detection result, and if any one of the nodding detection result, the gesture detection result and the lip language detection result passes the detection, determining that the confirmation action detection result passes the detection.
3. The method of claim 1, wherein the performing text rule matching on the speech text data to obtain a text matching result comprises:
and determining whether the voice text data accords with the matching rule according to a preset matching rule, wherein if the voice text data accords with the matching rule, the text matching result is that the matching is passed.
4. The method of claim 1, wherein generating a customer confirmation detection result based on the confirmation action detection result and the text matching result comprises:
and determining whether the detection result of the confirmation action is passed or not, or whether the text matching result is passed or not, and if the detection result of the confirmation action is passed or the text matching result is passed, determining that the generated detection result of the client is passed.
5. A customer confirmation detection apparatus in a double-record data quality inspection, the apparatus comprising:
the data acquisition module is used for acquiring double-recording data and decomposing the double-recording data into video data and audio data;
the action detection module is used for carrying out confirmation action detection on the video data to obtain a confirmation action detection result;
the rule matching module is used for carrying out voice recognition on the audio data to obtain voice text data and carrying out text rule matching on the voice text data to obtain a text matching result;
and the detection result module is used for generating a client confirmation detection result according to the confirmation action detection result and the text matching result.
6. The apparatus of claim 5, wherein the action detection module comprises:
the motion detection unit is used for performing nodding detection, gesture detection and lip language detection on the video data to respectively obtain a nodding detection result, a gesture detection result and a lip language detection result;
and the detection result unit is used for determining whether the confirmation action detection result passes the detection according to the nodding detection result, the gesture detection result and the lip language detection result, and if any one of the nodding detection result, the gesture detection result and the lip language detection result passes the detection, the confirmation action detection result passes the detection.
7. The apparatus of claim 5, wherein the rule matching module is further configured to determine whether the speech text data conforms to a preset matching rule, and if the speech text data conforms to the matching rule, the text matching result is a pass match.
8. The apparatus of claim 5, wherein the detection result module is further configured to determine whether the detection result of the confirmation action is a pass detection result or whether the matching result of the text is a pass matching result, and if the detection result of the confirmation action is a pass detection result or the matching result of the text is a pass matching result, the generated confirmation detection result of the customer is a pass.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 4.
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