Client appeal intelligent screening and answering method and system based on intelligent chest card

Abstract

The invention is suitable for the field of intelligent wearing, and provides an intelligent customer appeal screening and answering method and system based on an intelligent chest card, and the method comprises the steps: collecting and transmitting customer voice information in real time; converting the customer voice information into appeal text information, and synchronously analyzing the real-time emotional state of the customer; analyzing the appeal text information in multiple dimensions to generate key appeal content; searching and matching answer information of the key appeal content based on a pre-constructed knowledge reserve library, and performing emotion adaptation adjustment on the answer information according to the real-time emotion state of the customer; based on the key appeal content, generating an intelligent chest card association feedback action; according to the method and the system, the service response time is greatly shortened, service personnel can quickly obtain key appeals and respond in time, and the service efficiency is improved; through accurate sentiment analysis and adaptive answering, sentiment resonance with the customer is enhanced, the customer experience is optimized, and the service quality is promoted to be continuously improved.

Description

Technical Field

[0001] The present invention belongs to the field of smart wearables, and in particular relates to a method and system for intelligently identifying and answering customer demands based on a smart badge. Background Art

[0002] In today's business service environment, effective communication between customers and service personnel is crucial. Traditional customer service methods mainly rely on manual judgment and verbal communication. When facing a large number of customers, service personnel find it difficult to quickly and accurately identify customers' complex demands. Due to lack of experience or momentary negligence, service personnel may not be able to fully understand the customer's intentions, resulting in inaccurate or untimely answers, which reduces customer satisfaction.

[0003] With the development of artificial intelligence technology, although some intelligent customer service systems have emerged, most of them are based on online platforms and cannot be directly applied to face-to-face communication between service personnel and customers in offline service scenarios. In the offline service process, service personnel cannot obtain intelligent assistance in real time and can only rely on their own memory and limited training knowledge to respond to customer demands, which greatly limits the improvement of service efficiency and quality. Therefore, there is an urgent need to develop a method and system that can help service personnel quickly and accurately identify customer demands and intelligently answer them in face-to-face service scenarios. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for intelligently identifying and answering customer demands based on smart badges, aiming to solve the problems raised in the above-mentioned background technology.

[0005] The present invention is implemented in this way. On the one hand, a method for intelligently identifying and answering customer demands based on a smart badge comprises: The method comprises: Collect and send customer voice messages in real time; Convert customer voice information into text information and simultaneously analyze the customer's real-time emotional state; Analyze the text information of the appeal and generate key appeal content; Retrieve and match answer information of key demands based on the pre-built knowledge reserve, and adjust the answer information to match the customer's real-time emotional state; Generate smart badge-related feedback actions based on key demand content; Play the retrieved and emotion-adapted answer information.

[0006] As a further solution of the present invention, the converting of customer voice information into appeal text information and synchronous analysis of customer real-time emotional state specifically includes: Obtain customer voice information and convert it into text information based on deep learning speech recognition model; While converting the customer's voice information, extracting acoustic features of the converted customer's voice information, the acoustic features including pitch, volume, speech speed, and timbre; Based on the pre-built sentiment analysis model, extracted acoustic features and customer voice information, the customer's real-time emotional state is identified and the emotional state is classified into positive, negative or neutral categories.

[0007] As a further solution of the present invention, the analyzing of the appeal text information and generating key appeal content specifically includes: Based on natural language processing technology, the appeal text information is segmented; Perform part-of-speech tagging on the text after word segmentation to determine the grammatical function of each word or phrase in the sentence; Based on semantic analysis technology, key entities and relationships in the demand text information are extracted to identify the core objects and actions of customer needs; Integrate and filter the core objects and actions of customer needs, synthesize multiple related words or phrases, and combine them into key demand statements.

[0008] As a further solution of the present invention, the retrieving and matching the answer information of the key demand content based on the pre-constructed knowledge reserve library, and adjusting the answer information for emotional adaptation according to the real-time emotional state of the customer specifically include: Retrieve key demand expressions from the pre-constructed knowledge repository; The retrieved answer information of several key demand expressions is sorted according to the matching degree, and the answer information with the highest matching degree is selected; If the customer's real-time emotional state is in a negative emotional state, adjust the preset soothing language to adapt the answer information with the highest matching degree; If the customer's real-time emotional state is in a positive emotional state, adjust the preset enthusiastic language to adapt the answer information with the highest matching degree.

[0009] As a further solution of the present invention, the generating of the smart badge-related feedback action based on the key appeal content specifically includes: If the customer's real-time emotional state is in a negative emotional state, a red ring light command is generated and a manual explanation command is sent; If the customer's real-time emotional state is in a neutral emotional state, a ring light with yellow instructions is generated; If the customer's real-time emotional state is in a positive emotional state, a ring light with blue instructions is generated.

[0010] As a further solution of the present invention, on the other hand, a customer demand intelligent identification and answering system based on a smart badge, the system comprising: Real-time collection module, used to collect and send customer voice information in real time; Conversion module, used to convert customer voice information into demand text information; Synchronous analysis module, used to synchronously analyze the real-time emotional status of customers; Analysis module, used to analyze the appeal text information; The first generation module is used to generate key appeal content; The retrieval and matching module is used to retrieve and match the answer information of key demand contents based on the pre-constructed knowledge reserve library; The adaptation and adjustment module is used to adjust the response information emotionally according to the customer's real-time emotional state; The second generation module is used to generate smart badge-related feedback actions based on key appeal content; The playing module is used to play the answer information that has been retrieved and adjusted for emotion.

[0011] As a further solution of the present invention, the conversion module specifically includes: An acquisition unit, used for acquiring customer voice information; The conversion unit, based on a deep learning speech recognition model, converts the acquired customer voice information into demand text information.

[0012] As a further solution of the present invention, the synchronization analysis module specifically includes: An extraction unit, used for extracting acoustic features of the converted customer voice information while converting the customer voice information; A recognition unit, used to recognize the customer's real-time emotional state based on a pre-built emotional analysis model, extracted acoustic features, and customer voice information; A classification unit is used to classify the affective state into positive, negative, or neutral categories.

[0013] The present invention provides a method and system for intelligently identifying and answering customer demands based on smart badges. The method and system greatly shorten the service response time, and service personnel can quickly obtain key demands and respond in time, thereby improving service efficiency. Accurate sentiment analysis and adaptive answers enhance emotional resonance with customers, optimize customer experience, and promote continuous improvement in service quality. It has significant advantages in improving efficiency, optimizing experience, and continuous evolution. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a main flow chart of a method for intelligently identifying and answering customer demands based on smart badges.

[0015] Figure 2 The invention discloses a flow chart of a method for intelligently identifying and answering customer demands based on smart badges, which converts customer voice information into demand text information and simultaneously analyzes the customer's real-time emotional state.

[0016] Figure 3 The invention discloses a flowchart for analyzing text information of customer demands and generating key demand contents in a method for intelligently identifying and answering customer demands based on smart badges.

[0017] Figure 4 It is a flowchart of a method for intelligently identifying and answering customer demands based on smart badges, which retrieves and matches answer information of key demand contents based on a pre-constructed knowledge reserve library, and at the same time emotionally adapts the answer information according to the customer's real-time emotional state.

[0018] Figure 5 The invention discloses a flow chart of generating smart badge-related feedback actions based on key demand contents in a method for intelligently identifying and answering customer demands based on smart badges.

[0019] Figure 6 It is the main structure diagram of a customer demand intelligent identification and response system based on smart badges.

[0020] Figure 7 It is a structural block diagram of the conversion module in the customer demand intelligent identification and answering system based on smart badges.

[0021] Figure 8 It is a structural block diagram of the synchronous analysis module in the customer demand intelligent identification and answering system based on smart badges. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0023] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0024] The present invention provides a method and system for intelligently identifying and answering customer demands based on a smart badge, which solves the technical problems in the background technology.

[0025] like Figure 1 As shown, it is a main flow chart of a method for intelligently identifying and answering customer demands based on a smart badge provided by an embodiment of the present invention. The method for intelligently identifying and answering customer demands based on a smart badge includes: Step S100: Collect and send customer voice information in real time; Step S200: converting the customer's voice information into demand text information, and simultaneously analyzing the customer's real-time emotional state; Step S300: Analyze the appeal text information and generate key appeal content; Step S400: Retrieve and match answer information of key demand contents based on the pre-constructed knowledge reserve, and perform emotion adaptation adjustment on the answer information according to the real-time emotional state of the customer; Step S500: Generate smart badge-related feedback actions based on key appeal content; Step S600: Playing the retrieved and emotion-adapted answer information; When this embodiment is applied, a sound collection device is installed on the smart badge. First, the customer's voice information is collected accurately in real time. At the same time, the customer's voice information is stably transmitted to the background processing system with the help of wireless transmission modules using edge computing, dynamic spectrum allocation and other technologies. The background uses speech recognition and sentiment analysis models to convert voice information into text, and simultaneously analyzes the customer's emotional state. Afterwards, the text is analyzed to extract the key appeal content. Based on the key appeal, in the pre-built knowledge reserve library, matching answer information is retrieved through graph neural networks and semantic enhancement search technology, and emotional adaptation is adjusted according to the customer's emotional state. The smart badge will also generate associated feedback actions based on the key appeal, different light flashing and vibration modes, and finally play the adapted answer information through speech synthesis technology.

[0026] like Figure 2 As shown, as a preferred embodiment of the present invention, the converting of customer voice information into appeal text information and the simultaneous analysis of customer real-time emotional state specifically include: Step S201: Acquire customer voice information, and convert the acquired customer voice information into demand text information based on a deep learning speech recognition model; Step S202: while converting the customer's voice information, extracting acoustic features of the converted customer's voice information, the acoustic features including pitch, volume, speech speed, and timbre; Step S203: Based on the pre-built sentiment analysis model, the extracted acoustic features and the customer's voice information, the customer's real-time sentiment state is identified, and the sentiment state is classified into a positive category, a negative category or a neutral category; When this embodiment is applied, the customer's voice information is first obtained, and the collected voice is accurately converted into demand text information using a deep learning-based speech recognition model. During the voice information conversion process, acoustic features are extracted simultaneously, covering key elements such as pitch, volume, speaking speed, and timbre. These features provide an important basis for judging customer emotions. Finally, based on the pre-constructed sentiment analysis model, the extracted acoustic features and customer voice information are combined to identify the customer's real-time emotional state and classify it into positive, negative, or neutral categories. The pre-constructed sentiment analysis model uses machine learning algorithms to learn and model various emotional features, thereby achieving accurate judgment of customer emotions.

[0027] like Figure 3 As shown, as a preferred embodiment of the present invention, the analysis of the appeal text information and the generation of key appeal content specifically include: Step S301: Based on natural language processing technology, perform word segmentation processing on the appeal text information; Step S302: perform part-of-speech tagging on the segmented text to determine the grammatical function of each word or phrase in the sentence; Step S303: Based on semantic analysis technology, extract key entities and relationships in the demand text information, and identify the core objects and actions of customer needs; Step S304: Integrate and filter the core objects and actions of customer needs, synthesize multiple related words or related phrases, and combine them into key demand expressions; When this embodiment is applied, after completing the conversion of customer voice to demand text and the recognition of emotional state, the demand text information is segmented using natural language processing technology. Through the word segmentation tool, the continuous text is divided into independent words or phrases, breaking the coherence of the text and laying the foundation for subsequent detailed analysis. Then, the text after word segmentation is tagged with parts of speech. According to grammatical rules and lexical characteristics, the grammatical function of each word or phrase in the sentence is clarified, so as to understand the structure and semantic relationship of the text. Subsequently, based on semantic analysis technology, key entities and relationships are extracted from the demand text. By analyzing the meaning of words and context, the core objects of customer needs and the actions involved around the objects are identified, and the key elements of customer needs are defined. Finally, the extracted core objects and actions of customer needs are integrated and screened. Remove irrelevant information, organically combine multiple related words or phrases, and form an accurate expression of key demands.

[0028] like Figure 4 As shown, as a preferred embodiment of the present invention, the method of retrieving and matching answer information of key appeal content based on the pre-constructed knowledge reserve library and adjusting the answer information for emotional adaptation according to the real-time emotional state of the customer specifically includes: Step S401: Retrieve key demand expressions in the pre-built knowledge repository; Step S402: sorting the retrieved answer information of the key demand expressions according to the matching degree, and selecting the answer information with the highest matching degree; Step S403: If the customer's real-time emotional state is in a negative emotional state, adjust the preset soothing language to adapt the answer information with the highest matching degree; Step S404: if the customer's real-time emotional state is in a positive emotional state, adjusting the preset enthusiastic language to adapt the answer information with the highest matching degree; It should be understood that, first, the key demand expressions are retrieved in the pre-constructed knowledge reserve. The knowledge reserve stores a large amount of information related to common customer needs. Through efficient retrieval algorithms, it can quickly locate the content related to the key demand expressions and provide a basis for subsequent answers. The answer information of several key demand expressions retrieved is sorted according to the matching degree. The matching degree is calculated based on multiple factors such as keyword matching and semantic similarity to ensure that the most relevant answer information is ranked first, so that the answer information with the highest matching degree can be quickly selected to improve service efficiency. Then, the answer information is adapted and adjusted according to the real-time emotional state of the customer. If the customer is in a negative emotional state, by adding preset soothing language, such as "I am very sorry for the inconvenience" and "Please don't worry", the answer is made more humane and the negative emotions of the customer are alleviated. If the customer is in a positive emotional state, the preset enthusiastic language, such as "Thank you very much for your support" and "I am glad to serve you", is incorporated to further enhance the customer's favorability and improve the customer experience.

[0029] like Figure 5 As shown in FIG. 1 , as a preferred embodiment of the present invention, the generating of the smart badge-related feedback action based on the key appeal content specifically includes: Step S501: if the customer's real-time emotional state is in a negative emotional state, a ring light red instruction is generated and a manual explanation instruction is sent; Step S502: if the customer's real-time emotional state is in a neutral emotional state, a yellow ring light instruction is generated; Step S503: if the customer's real-time emotional state is in a positive emotional state, a ring light with a blue instruction is generated; When this embodiment is applied, if the customer is in a negative emotional state, in addition to adding preset soothing language to the answer information, a ring light with red instructions will be generated to remind the staff with a striking visual signal that the customer is in a bad mood. At the same time, manual explanation instructions will be sent to arrange for professional personnel to intervene and provide customers with more detailed and humane services, thereby effectively soothing the customer's emotions and solving problems. If the customer is in a neutral emotional state, a ring light with yellow instructions will be generated, which will serve as a gentle reminder, allowing the staff to serve the customer with a stable and professional attitude and maintain a good communication atmosphere. If the customer is in a positive emotional state, enthusiastic language will be incorporated into the answer to enhance the customer's favorability. At the same time, a ring light with blue instructions will be generated to convey a positive and pleasant atmosphere, allowing the customer to further feel the high-quality service and enhance the customer experience.

[0030] like Figure 6 As shown, as another preferred embodiment of the present invention, on the other hand, a customer demand intelligent identification and answering system based on a smart badge, the system comprises: Real-time collection module 100, used for collecting and sending customer voice information in real time; The conversion module 200 is used to convert the customer's voice information into the demand text information; Synchronous analysis module 300, used for synchronously analyzing the real-time emotional state of customers; An analysis module 400 is used to analyze the appeal text information; The first generating module 500 is used to generate key appeal content; A search and matching module 600 is used to search and match answer information of key appeal contents based on a pre-built knowledge reserve library; Adaptation and adjustment module 700, used to perform emotional adaptation and adjustment on the answer information according to the real-time emotional state of the customer; The second generating module 800 is used to generate a smart badge-related feedback action based on the key appeal content; A playing module 900 is used to play the answer information that has been retrieved and adjusted for emotion adaptation; When this embodiment is applied, the real-time collection module 100 collects and sends customer voice information in real time, the conversion module 200 converts the customer voice information into demand text information, the synchronous analysis module 300 synchronously analyzes the customer's real-time emotional state, the analysis module 400 analyzes the demand text information, the first generation module 500 generates key demand content, based on the pre-constructed knowledge reserve library, the retrieval and matching module 600 retrieves and matches the answer information of the key demand content, the adaptation and adjustment module 700 performs emotional adaptation and adjustment on the answer information according to the customer's real-time emotional state, based on the key demand content, the second generation module 800 generates a smart badge-related feedback action, and the playback module 900 plays the retrieved and emotionally adapted answer information.

[0031] like Figure 7 As shown, as another preferred embodiment of the present invention, the conversion module 200 specifically includes: The acquisition unit 201 is used to acquire the customer's voice information; The conversion unit 202 converts the acquired customer voice information into demand text information based on a deep learning speech recognition model.

[0032] When this embodiment is applied, the acquisition unit 201 acquires customer voice information, and based on the deep learning speech recognition model, the conversion unit 202 converts the acquired customer voice information into demand text information.

[0033] like Figure 8 As shown, as another preferred embodiment of the present invention, the synchronization analysis module 300 specifically includes: The extraction unit 301 is used to extract the acoustic features of the converted customer voice information while converting the customer voice information; The recognition unit 302 is used to recognize the real-time emotional state of the customer based on the pre-built emotional analysis model, the extracted acoustic features and the customer's voice information; The classification unit 303 is used to classify the emotional state into a positive category, a negative category or a neutral category.

[0034] The above-mentioned embodiment of the present invention provides a method for intelligently identifying and answering customer demands based on a smart badge, and provides a system for intelligently identifying and answering customer demands based on a smart badge. A sound collection device is installed on the smart badge. First, the customer's voice information is accurately collected in real time. At the same time, with the help of a wireless transmission module using edge computing, dynamic spectrum allocation and other technologies, the customer's voice information is stably transmitted to the background processing system. The background uses speech recognition and sentiment analysis models to convert voice information into text, and simultaneously analyzes the customer's emotional state. Afterwards, the text is analyzed to extract the key demand content. According to the key demands, in the pre-constructed knowledge reserve, the matching answer information is retrieved through the graph neural network and semantic enhancement search technology, and the emotional adaptation adjustment is performed according to the customer's emotional state. The smart badge will also generate associated feedback actions based on key demands, different light flashing and vibration modes, and finally play the adapted answer information through speech synthesis technology; this method and system greatly shortens the service response time, and service personnel can quickly obtain key demands and respond in time, improving service efficiency; accurate sentiment analysis and adaptive answers enhance emotional resonance with customers, optimize customer experience, and promote continuous improvement in service quality, with significant advantages in improving efficiency, optimizing experience and continuous evolution.

[0035] In order to load the above-mentioned method and system and enable it to run smoothly, the system, in addition to the various modules mentioned above, may also include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, processors and memories, etc.

[0036] The processor may be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the system, and various interfaces and lines are used to connect various parts.

[0037] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0038] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0039] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for intelligently identifying and answering customer demands based on smart badges, characterized in that: The method comprises: Collect and send customer voice messages in real time; Convert customer voice information into text information and simultaneously analyze the customer's real-time emotional state; Analyze the text information of the appeal and generate key appeal content; Retrieve and match answer information of key demands based on the pre-built knowledge reserve, and adjust the answer information to match the customer's real-time emotional state; Generate smart badge-related feedback actions based on key demand content; Play the retrieved and emotion-adapted answer information.

2. The method for intelligently identifying and answering customer demands based on smart badges according to claim 1 is characterized in that: The converting of the customer's voice information into the demand text information and the simultaneous analysis of the customer's real-time emotional state specifically include: Obtain customer voice information and convert it into text information based on deep learning speech recognition model; While converting the customer's voice information, extracting acoustic features of the converted customer's voice information, the acoustic features including pitch, volume, speech speed, and timbre; Based on the pre-built sentiment analysis model, extracted acoustic features and customer voice information, the customer's real-time emotional state is identified and the emotional state is classified into positive, negative or neutral categories.

3. The method for intelligently identifying and answering customer demands based on smart badges according to claim 1 is characterized in that: The analyzing of the demand text information and generating key demand content specifically includes: Based on natural language processing technology, the appeal text information is segmented; Perform part-of-speech tagging on the text after word segmentation to determine the grammatical function of each word or phrase in the sentence; Based on semantic analysis technology, key entities and relationships in the demand text information are extracted to identify the core objects and actions of customer needs; Integrate and filter the core objects and actions of customer needs, synthesize multiple related words or phrases, and combine them into key demand statements.

4. The method for intelligently identifying and answering customer demands based on smart badges according to claim 2 is characterized in that: The retrieving and matching the answer information of the key demand content based on the pre-constructed knowledge reserve library and adjusting the answer information for emotion adaptation according to the real-time emotional state of the customer specifically include: Retrieve key demand expressions from the pre-constructed knowledge repository; The retrieved answer information of several key demand expressions is sorted according to the matching degree, and the answer information with the highest matching degree is selected; If the customer's real-time emotional state is in a negative emotional state, adjust the preset soothing language to adapt the answer information with the highest matching degree; If the customer's real-time emotional state is in a positive emotional state, adjust the preset enthusiastic language to adapt the answer information with the highest matching degree.

5. The method for intelligently identifying and answering customer demands based on smart badges according to claim 2 is characterized in that: The generating of the smart badge-related feedback action based on the key demand content specifically includes: If the customer's real-time emotional state is in a negative emotional state, a red ring light command is generated and a manual explanation command is sent; If the customer's real-time emotional state is in a neutral emotional state, a ring light with yellow instructions is generated; If the customer's real-time emotional state is in a positive emotional state, a ring light with blue instructions is generated.

6. A customer demand intelligent identification and answering system based on smart badges, characterized in that: The method for intelligently identifying and answering customer demands based on smart badges as described in any one of claims 1 to 5 is applied, wherein the system comprises: Real-time collection module, used to collect and send customer voice information in real time; Conversion module, used to convert customer voice information into demand text information; Synchronous analysis module, used to synchronously analyze the real-time emotional status of customers; Analysis module, used to analyze the appeal text information; The first generation module is used to generate key appeal content; The retrieval and matching module is used to retrieve and match the answer information of key demand contents based on the pre-constructed knowledge reserve library; The adaptation and adjustment module is used to adjust the response information emotionally according to the customer's real-time emotional state; The second generation module is used to generate smart badge-related feedback actions based on key appeal content; The playing module is used to play the answer information that has been retrieved and adjusted for emotion.

7. The intelligent identification and answering system for customer demands based on smart badges according to claim 6 is characterized in that: The conversion module specifically includes: An acquisition unit, used for acquiring customer voice information; The conversion unit, based on a deep learning speech recognition model, converts the acquired customer voice information into demand text information.

8. The intelligent identification and answering system for customer demands based on smart badges according to claim 6 is characterized in that: The synchronization analysis module specifically includes: An extraction unit, used for extracting acoustic features of the converted customer voice information while converting the customer voice information; A recognition unit, used to recognize the customer's real-time emotional state based on the pre-built emotional analysis model, the extracted acoustic features and the customer's voice information; A classification unit is used to classify the affective state into positive, negative, or neutral categories.

Images