WO2021135317A1 - Procédé et système d'établissement d'un appel sur la base d'une commande - Google Patents

Procédé et système d'établissement d'un appel sur la base d'une commande Download PDF

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Publication number
WO2021135317A1
WO2021135317A1 PCT/CN2020/111942 CN2020111942W WO2021135317A1 WO 2021135317 A1 WO2021135317 A1 WO 2021135317A1 CN 2020111942 W CN2020111942 W CN 2020111942W WO 2021135317 A1 WO2021135317 A1 WO 2021135317A1
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WIPO (PCT)
Prior art keywords
order
voice
consignee
reply
delivery
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PCT/CN2020/111942
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English (en)
Chinese (zh)
Inventor
邱会会
倪合强
李斌
白云
李宝军
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苏宁云计算有限公司
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Priority to CA3166344A priority Critical patent/CA3166344A1/fr
Publication of WO2021135317A1 publication Critical patent/WO2021135317A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
    • G06F16/3329—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3343—Query execution using phonetics
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L13/00—Speech synthesis; Text to speech systems
    • G10L13/02—Methods for producing synthetic speech; Speech synthesisers
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • 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
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • 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
    • G10L15/18—Speech classification or search using natural language modelling
    • G10L15/1822—Parsing for meaning understanding
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/223—Execution procedure of a spoken command

Definitions

  • the present invention relates to the field of intelligent voice, in particular to a method and system for making calls based on orders.
  • the above three methods will have some problems that need to be solved: when sending delivery information through the first type of SMS, the user now has too many SMS messages to pay attention to the delivery information in time, and the user has a bunch of SMS messages, such as advertising push SMS, marketing Users will not respond easily to text messages, fraudulent text messages, etc., and also reduce the frequency of checking text messages.
  • the second type of mobile phone APP pushes delivery information, some users activate the message reminder function, which can receive the message in time, but the user cannot see it in time; some users do not activate the message reminder, and can only see the message after the user logs in to the system , Not in time.
  • the mobile phone number is 11 digits. A courier has hundreds of orders a day. Direct manual calls will result in too slow efficiency. Some couriers still ride bicycles. When you make a call, traffic safety is more dangerous. How to quickly and efficiently deliver the last mile of express delivery requires further technological innovation.
  • the embodiments of the present invention provide a method and system for making a call based on an order, which can automatically dial the order information and realize the combination of machine and manual communication, and improve the efficiency of delivery.
  • the technical solution adopted by the present invention is:
  • an embodiment of the present invention provides a method for making a call based on an order, which includes the following steps:
  • Extract the keywords of the voice information extract the reply voice from the reply vocabulary corresponding to the keywords and send it to the consignee;
  • the machine dialogue is converted into a manual dialogue.
  • the distribution strategy includes:
  • the machine recognition of the voice information is realized by a voice recognition model, and the establishment of the voice recognition model includes: collecting voice information between the consignee and the delivery person, training the voice information and storing it.
  • the machine recognition further includes a semantic understanding of the voice information, and the semantic understanding is realized through a voice rule configuration and a voice similarity algorithm.
  • the reply voice included in the reply vocabulary is a text conversion through a voice text, and the text of the voice text is determined according to the transcript or the end of the conversation during the communication between the consignee and the delivery person.
  • an embodiment of the present invention also provides a system for making a call based on an order, including:
  • the order scanning module is used to scan the order number to obtain and save the order address and the phone number corresponding to the order, and automatically dial the phone number based on the delivery strategy of the order;
  • the machine recognition module is used to automatically connect and machine recognize the voice information of the consignee corresponding to the telephone number, and start a machine dialogue;
  • the machine reply module is used to extract the keywords of the voice message, extract the reply voice from the reply vocabulary corresponding to the keywords and send it to the consignee;
  • the manual conversion module is used to convert the machine dialogue into a manual dialogue when the machine reply module cannot extract the reply voice from the reply lexicon and reply to the consignee.
  • the order scanning module includes a delivery strategy selection unit, and the selection of the order delivery by the delivery strategy selection unit includes: order delivery according to the distance from the receiving place to the delivery station; order according to the order number scanning order Delivery; the historical call-through rate of the consignee's answering calls is smoothly delivered in sequence; the delivery is in sequence according to the recipient's user tag level.
  • the recognition of the voice information by the machine recognition module is realized through a voice recognition model, and the establishment of the voice recognition model includes: collecting voice information between the consignee and the dispatcher, training the voice information and storing it .
  • machine recognition module is also used for semantic understanding of the voice information, and the semantic understanding is realized through voice rule configuration and voice similarity algorithm.
  • the extraction of the reply voice by the machine reply module includes converting the text of the voice text into a reply voice, and the text of the voice text is based on the transliteration or closing speech of the consignee and the delivery person. The technique is determined.
  • the embodiment of the present invention discloses a method and system for making a call based on an order.
  • the order is first scanned to determine the phone number to be dialed and the delivery address, and after the consignee is connected through
  • the machine communicates with the consignee, and extracts the key words of the consignee’s voice information.
  • the key words are used to complete the reply to the consignee. Once the machine is unable to communicate with the consignee, it will switch to manual operation through the delivery person. Communicate manually with the consignee.
  • This kind of first communication between the machine and the consignee by phone can significantly improve the efficiency of the distribution during the delivery process of the courier, save the delivery time of the courier, and avoid the consignee from being unable to receive the goods in time during the distribution process.
  • the shortcomings of information, and the direct call through the order improves the success rate of a delivery, reduces the risk of personal information leakage of the consignee, improves the professional service skills of the delivery staff, and reduces the rate of customer complaints.
  • FIG. 1 is a schematic flowchart of a method for making a call based on an order disclosed in an embodiment of the present invention
  • FIG. 2 is a logical schematic diagram of machine communication in the method for making a call based on an order disclosed in an embodiment of the present invention
  • Fig. 3 is a schematic diagram of the structural execution of the system for dialing a call based on an order disclosed in an embodiment of the present invention.
  • this embodiment provides a method for making a call based on an order, which includes the following steps:
  • S1 Scan the order number to obtain and save the order address and the phone number corresponding to the order, and automatically dial the phone number based on the delivery strategy of the order;
  • S2 Automatically connect and the machine recognizes the voice information of the consignee corresponding to the telephone number, and starts a machine dialogue;
  • the order is first scanned to determine the phone number to be called and the delivery address, after the consignee is connected, the machine communicates with the consignee through the machine, and the consignee’s information is retrieved.
  • the key words of the voice message are used to complete the reply to the consignee.
  • the machine cannot communicate with the consignee, it will switch to manual, and the delivery person and the consignee can communicate manually.
  • This kind of first communication between the machine and the consignee by phone can significantly improve the efficiency of the distribution during the delivery process of the courier, save the delivery time of the courier, and avoid the consignee from being unable to receive the goods in time during the distribution process.
  • the shortcomings of information, and the direct call through the order improves the success rate of a delivery, reduces the risk of personal information leakage of the consignee, improves the professional service skills of the delivery staff, and reduces the rate of customer complaints.
  • the distribution strategy includes: sequential distribution according to the distance from the receiving place to the distribution station; or sequential distribution according to the order number scanning sequence; or smooth sequential distribution according to the historical call-through rate of the consignee answering the phone ; Or according to the consignee’s user tag level for delivery.
  • the above-mentioned delivery automatic call can be realized through a specific APP downloaded by a mobile phone, a delivery terminal, etc.
  • the delivery person can do it according to his own delivery needs.
  • the choice of distribution strategy improves the satisfaction of the consignee while improving the efficiency of distribution.
  • the machine recognition of the voice information is realized by a voice recognition model, and the establishment of the voice recognition model includes: collecting voice information between a consignee and a delivery person, training the voice information and storing it. Further, the machine recognition further includes a semantic understanding of the voice information, and the semantic understanding is realized through a voice rule configuration and a voice similarity algorithm.
  • Figure 2 is a logical schematic diagram of the courier's machine communication.
  • the voice recognition model of the consignee is mainly limited to the delivery time and location.
  • the machine's understanding of the consignee is also limited. Once the machine recognizes The voice of the consignee cannot be ignored. For example, there is no response from the machine after a delay of about 5 seconds or the consignee directly hangs up the phone.
  • the delivery staff will manually confirm the delivery information with the consignee.
  • This process saves time mainly in: it can reduce the time of pressing the button for 5-8 seconds before making a call; it can reduce the time of making a call and the user's answering by 5 seconds; after the end of the communication with the user, it can reduce the recording time by 5-8 seconds Time; it can reduce the time for special phone calls. For example, when picking goods, you can make a phone call while picking the goods. In addition, you can improve the service level and unify the language and tone of the call.
  • the reply voice included in the reply vocabulary is a text conversion through voice text, and the text of the voice text is determined according to the transcript or end of the conversation when the consignee and the delivery person communicate.
  • the reply voice is a voice converted from text, where the text includes both
  • the common words of the consignee also include the common words of the delivery staff, such as the delivery location: rookie station, property management office, express cabinet, etc., and also include the delivery time.
  • the process of machine dialogue is mainly based on the common delivery terms summarized after the manual dialogue between the delivery person and the delivery person after the machine learning.
  • this embodiment provides a system for dialing calls based on orders, including:
  • the order scanning module 1 is used to scan the order number to obtain and save the order address and the phone number corresponding to the order, and automatically dial the phone number based on the delivery strategy of the order;
  • the machine recognition module 2 is used to automatically connect and machine recognize the voice information of the consignee corresponding to the telephone number, and start a machine dialogue;
  • the machine reply module 3 is used to extract the keywords of the voice information, extract the reply voice from the lexicon corresponding to the keywords, and send it to the consignee;
  • the manual conversion module 4 is used for converting the machine dialogue into a manual dialogue when the machine reply module 3 cannot extract the reply voice from the reply lexicon and reply to the consignee.
  • the courier can use the system for delivery. You can choose the traditional manual delivery.
  • the system is used for delivery.
  • the order is scanned to determine the phone number to be called and the delivery address.
  • the machine communicates with the consignee through the machine, and extracts the key words of the consignee’s voice information, and completes the reply to the consignee through the key words.
  • the machine cannot communicate with the consignee, switch to manual.
  • Manual communication between the delivery staff and the consignee This kind of first communication between the machine and the consignee by phone can significantly improve the efficiency of the distribution during the delivery process of the courier, save the delivery time of the courier, and avoid the consignee from being unable to receive the goods in time during the distribution process.
  • the shortcomings of information, and the direct call through the order improves the success rate of a delivery, reduces the risk of personal information leakage of the consignee, improves the professional service skills of the delivery staff, and reduces the rate of customer complaints.
  • the order scanning module 1 includes a distribution strategy selection unit 11, and the selection of the distribution strategy selection unit 11 for order distribution includes: order delivery according to the distance from the receiving place to the distribution station; scanning according to the order number Delivery is in sequence; the historical call-through rate of the consignee is smoothly delivered in sequence; delivery is in sequence according to the user tag level of the consignee.
  • the delivery staff can manually initiate automatic dialing. At this time, the operation time is relatively variable, and they can also manually initiate automatic dialing. Or start automatic dialing regularly, and set the automatic dialing time according to the working time. After scanning the order code, the delivery staff can choose the delivery strategy according to their own delivery needs, which can improve the satisfaction of the consignee while providing delivery efficiency.
  • the recognition of the voice information by the machine recognition module 2 is realized through a voice recognition model, and the establishment of the voice recognition model includes: collecting voice information between the consignee and the delivery person, training the voice information and storage. Further, the machine recognition module 2 is also used for semantic understanding of the voice information, which is realized through voice rule configuration and voice similarity algorithm.
  • the voice recognition model of the consignee's voice recognition is mainly limited to the delivery time and delivery location. The machine's understanding of the consignee is also limited. Once the machine cannot recognize the consignee's voice, for example, the machine is still not performed after a delay of about 5 seconds. Or the consignee directly hung up the phone, which will be converted to manual communication. The delivery staff will manually confirm the delivery information with the consignee.
  • This process saves time mainly in: it can reduce the number of calls Before pressing the key for 5-8 seconds; it can reduce the time of making a call and answering the user by 5 seconds; after communicating with the user, it can reduce the recording time by 5-8 seconds; it can reduce the time for special calls, such as when picking goods , Make calls while picking goods, in addition, you can also improve the service level, and unify the language and tone of the call.
  • the machine reply module 3 before the machine reply module 3 extracts the reply voice, it includes converting the text of the voice text into reply voice, and the text of the voice text is based on the transliteration or termination of the communication between the consignee and the delivery person.
  • the words are ok.
  • the reply voice is a voice converted from text, where the text includes both
  • the common words of the consignee also include the common words of the delivery staff, such as the delivery location: rookie station, property management office, express cabinet, etc., and also include the delivery time.
  • the process of machine dialogue is mainly based on the common delivery terms summarized after the manual dialogue between the delivery person and the delivery person after the machine learning.
  • the system for dialing calls based on orders provided in the above embodiment only uses the division of the above functional modules for example when delivering express delivery or takeaway.
  • the above functional assignments can be divided into different groups according to needs.
  • the function module is completed, that is, the internal structure of the system for making calls based on orders is divided into different function modules to complete all or part of the functions described above.
  • the system for dialing a call based on an order provided in the above embodiment belongs to the same concept as the embodiment of the method for dialing a call based on an order. For the specific implementation process, please refer to the method embodiment, which will not be repeated here.
  • the program can be stored in a computer-readable storage medium.
  • the storage medium mentioned can be a read-only memory, a magnetic disk or an optical disk, etc.

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Abstract

La présente invention concerne un procédé et un système d'établissement d'un appel sur la base d'une commande. Le procédé comporte les étapes consistant à : scruter un numéro de commande pour acquérir et stocker une adresse de commande et un numéro de téléphone correspondant à une commande, et composer automatiquement le numéro de téléphone sur la base d'une politique de livraison de la commande (S1); connecter automatiquement l'appel et reconnaître, au moyen d'une machine, des informations de parole d'un destinataire correspondant au numéro de téléphone, et commencer une conversation automatisée (S2); extraire un mot-clé des informations de parole, extraire un élément de parole de réponse d'une réserve de mots de réponse correspondant au mot-clé, et envoyer la parole de réponse au destinataire (S3); et lorsque la parole de réponse ne peut pas être extraite de la réserve de mots de réponse, et qu'il n'est pas possible de répondre au destinataire, convertir la conversation automatisée en une conversation manuelle (S4). En réalisant en premier lieu une communication téléphonique entre une machine et un destinataire, pendant un processus de livraison d'un livreur, le rendement de livraison peut être significativement amélioré, et le temps de livraison du livreur peut être réduit; et le fait d'établir directement un appel au moyen d'un commande améliore le taux de succès d'une instance de livraison, le risque de fuites d'informations personnelles du destinataire est réduit, et le niveau de service professionnel du livreur est amélioré.
PCT/CN2020/111942 2019-12-30 2020-08-28 Procédé et système d'établissement d'un appel sur la base d'une commande WO2021135317A1 (fr)

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CN201911396164.XA CN111178807A (zh) 2019-12-30 2019-12-30 一种基于订单拨打电话的方法和系统
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CN111178807A (zh) * 2019-12-30 2020-05-19 苏宁云计算有限公司 一种基于订单拨打电话的方法和系统
WO2022000140A1 (fr) * 2020-06-28 2022-01-06 北京来也网络科技有限公司 Méthode de dépistage épidémique et appareil combinant rpa avec ai
CN112435093A (zh) * 2020-11-24 2021-03-02 广州易尊网络科技股份有限公司 一种电子订单的异步处理方法及装置
TWI809465B (zh) * 2021-08-04 2023-07-21 台灣大哥大股份有限公司 物流資訊通知系統及方法

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