CN114025050A - Speech recognition method and device based on intelligent outbound and text analysis - Google Patents
Speech recognition method and device based on intelligent outbound and text analysis Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/527—Centralised call answering arrangements not requiring operator intervention
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
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- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/16—Speech classification or search using artificial neural networks
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- 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
- G10L15/26—Speech to text systems
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Abstract
The invention discloses a voice recognition method based on intelligent outbound and text analysis, which comprises the following steps: acquiring a first voice stream of a call between an AI robot and a target client, wherein the first voice stream is obtained by the AI robot through calling out the target client based on a preset AI technique; converting the first voice stream into a first text, and sending the first text to a text analysis robot model for processing to obtain a classification label of the first text and a classification accuracy of the first text, wherein the analysis robot comprises a preconfigured analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used for describing an intention category of the target client.
Description
Technical Field
The application relates to the field of intelligent outbound, in particular to a voice recognition method and device based on intelligent outbound and text analysis.
Background
The existing intelligent outbound system mainly carries out outbound by matching an AI robot with a conversation, a circuit and the like, can realize repeated outbound work in large batch under limited resources, and greatly reduces the labor and time cost. However, the outbound is only a marketing means, and not a final purpose, and for the merchant, it is important to find a new business opportunity after how to implement a marketing purpose in the outbound process, and the existing outbound system cannot implement the identification of the business opportunity.
At present, there are many tools for imaging (labeling) customers through text analysis so as to realize accurate positioning of customers and further discover business opportunities. However, the above schemes mostly perform recognition after manually acquiring a text, and cannot be effectively combined with an intelligent outbound system to realize automatic business recognition after the outbound is finished. How to effectively combine intelligent callouts with text analysis is the next direction of research.
Disclosure of Invention
The technical problem to be solved by the embodiment of the application is to provide a voice recognition method and a voice recognition device based on intelligent outbound and text analysis, so as to solve the technical problem that the existing intelligent outbound and text analysis cannot be effectively combined to realize automatic business recognition after the outbound.
In order to achieve the above purpose, the embodiments of the present application adopt the following technical solutions:
in a first aspect, an embodiment of the present application provides a speech recognition method based on intelligent outbound and text analysis, where the method includes:
acquiring a first voice stream of a call between an AI robot and a target client, wherein the first voice stream is obtained by the AI robot through calling out the target client based on a preset AI technique;
converting the first voice stream into a first text, and sending the first text to a text analysis robot model for processing to obtain a classification label of the first text and a classification accuracy of the first text, wherein the analysis robot comprises a preconfigured analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used for describing an intention category of the target client.
In a second aspect, an embodiment of the present application provides a speech recognition apparatus based on intelligent outbound and text analysis, the apparatus includes:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a first voice stream of a call between an AI robot and a target client, and the first voice stream is obtained by calling the target client out through the AI robot based on a preset AI technique;
a first conversion unit, configured to convert the first voice stream into a first text;
the first sending unit is used for sending the first text to a text analysis robot model for processing to obtain a classification label of the first text and the classification accuracy of the first text, wherein the analysis robot comprises a preset analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or a plurality of text corpora, and the classification label is used for describing the intention category of the user target.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory, where the memory stores at least one instruction, at least one program, a set of codes to be executed, or a set of instructions, and the at least one instruction, the at least one program, the set of codes to be executed, or the set of instructions is executed by the processor to implement the method for speech recognition based on intelligent outbound and text analysis as described in the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which at least one instruction, at least one program, a set of codes, or a set of instructions is stored, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is executed by a processor to implement the method for speech recognition based on intelligent callout and text analysis as described in the first aspect.
The beneficial effects of the embodiment of the application are that: the embodiment of the application provides a voice recognition method and a voice recognition device based on intelligent outbound and text analysis.
Drawings
FIG. 1 is a schematic flow chart illustrating a speech recognition method based on intelligent outbound and text analysis according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a speech recognition apparatus based on intelligent outbound and text analysis according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions of the present application are further described in detail with reference to the following specific embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present application, but 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 application.
The application provides a voice recognition method and device based on intelligent outbound and text analysis, and aims to solve the technical problem that the existing intelligent outbound and text analysis cannot be effectively combined to realize automatic business recognition after the outbound.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of a speech recognition method based on intelligent outbound and text analysis according to an embodiment of the present application is shown, where the method includes:
step S101, a first voice stream of a call between an AI robot and a target client is obtained, wherein the first voice stream is obtained by calling the target client out through the AI robot based on a preset AI technique;
it is to be understood that the first voice stream is a voice stream generated during the communication between the AI robot and the target client, and includes a voice stream of the AI robot and a voice stream of the target client.
Step S102, converting the first voice stream into a first text, and sending the first text to a text analysis robot model for processing to obtain a classification label of the first text and a classification accuracy of the first text, wherein the analysis robot comprises a preconfigured analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used for describing an intention category of the target client.
With respect to step S102, the first voice stream is converted into a first text through voice to text.
In one embodiment, the category label includes any one of a consultation of a commodity, an intention to purchase, and a complaint suggestion.
In one embodiment, the text analysis model is parametrically adjusted by the classification label of the first text and the classification accuracy of the first text.
It can be understood that the parameters of the text analysis model are adjusted by the classification label and the classification accuracy of the first text, so that the text analysis model is optimized.
In one embodiment, prior to the AI robot making an outbound call to the target customer based on a preset AI conversation:
creating an outbound task, and configuring a preset AI speech and an outbound line for the AI robot;
and introducing the outbound information of the target client into the AI robot to execute an outbound task.
It is understood that the outbound information of the target client may include the name, outbound number, hobbies, etc. of the target client, which is not limited in this application.
Referring to fig. 2, a schematic structural diagram of a speech recognition apparatus based on intelligent outbound and text analysis according to an embodiment of the present application is shown, where the apparatus includes:
a first obtaining unit 201, configured to obtain a first voice stream for a call between the AI robot and a target client, where the first voice stream is obtained
The first voice flow is obtained by calling out the target client through the AI robot based on a preset AI technique;
a first conversion unit 202, configured to convert the first voice stream into a first text;
the first sending unit 203 is configured to send the first text to a text analysis robot model for processing to obtain a classification label of the first text and a classification accuracy of the first text, where the analysis robot includes a preconfigured analysis rule and a text analysis model, the analysis rule is used to output the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used to describe an intention category of the target client.
Referring to fig. 3, a schematic structural diagram of an electronic device according to an embodiment of the present application is shown, where the electronic device may include: at least one network interface 302, memory 303, and at least one processor 301. The various components in the electronic device are coupled together by a bus system 304. It will be appreciated that the bus system 304 is used to enable communications among the components. The bus system 304 includes a power bus, a control bus, and a status signal bus in addition to a data bus, but for clarity of illustration, the various buses are labeled as bus system 304 in FIG. 3.
In some embodiments, memory 303 stores elements, executable modules or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system 3031 and application programs 3032.
The operating system 3031 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is configured to implement various outgoing services and process hardware-based tasks. The application 3032 includes various applications, such as a Media Player (Media Player), a Browser (Browser), and the like, and implements various application services. The program for implementing the method of the embodiment of the present application may be included in an application program.
In the above embodiment, the electronic device further includes: at least one instruction, at least one program, set of codes, or set of instructions stored on the memory 303 that is executable by the processor 301 to perform the steps of implementing any of the intelligent callout and text analysis based speech recognition methods described in the embodiments of the present application.
In one embodiment, the present application further provides a computer-readable storage medium having at least one instruction, at least one program, a set of codes, or a set of instructions stored therein, which when executed by a processor, implement the steps of any of the intelligent callout and text analysis based speech recognition methods described in the embodiments of the present application.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, and that the at least one instruction, the at least one program, the code set, or the instruction set may be stored in a non-volatile computer-readable storage medium, and when executed, the at least one instruction, the at least one program, the code set, or the instruction set may implement the steps of any of the mapping methods described in the embodiments of the present application. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are only illustrative and not restrictive; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, which are within the protection scope of the present application.
Claims (8)
1. A speech recognition method based on intelligent outbound and text analysis is characterized by comprising the following steps:
acquiring a first voice stream of a call between the AI robot and a target client, wherein the first voice stream passes through
The AI robot carries out outbound acquisition on the target client based on a preset AI operation;
converting the first voice stream into a first text, and sending the first text to a text analysis robot
The model is processed to obtain a classification label of the first text and the classification accuracy of the first text, wherein the analysis robot comprises a preconfigured analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used for describing the intention category of the target client.
2. The method of claim 1, wherein the speech recognition method based on intelligent outbound and text analysis
Characteristically, the first voice stream is converted to first text by voice to text.
3. The method of claim 1, wherein the speech recognition method based on intelligent outbound and text analysis
Characteristically, the method further comprises: and performing parameter adjustment on the text analysis model through the classification label of the first text and the classification accuracy of the first text.
4. The method of claim 1, wherein the speech recognition method based on intelligent outbound and text analysis
Characterized in that, before the AI robot makes an outbound call to the target customer based on a preset AI conversation:
creating an outbound task, and configuring a preset AI speech and an outbound line for the AI robot;
and introducing the outbound information of the target client into the AI robot to execute an outbound task.
5. The method of claim 1, wherein the speech recognition method based on intelligent outbound and text analysis
The classification label comprises any one of commodity consultation, purchase intention and complaint suggestion.
6. A speech recognition device based on intelligent outbound and text analysis, the device comprising:
a first acquisition unit for acquiring a first voice stream of a call between the AI robot and a target client, wherein
The first voice flow is obtained by calling out the target client through the AI robot based on a preset AI technique;
a first conversion unit, configured to convert the first voice stream into a first text;
a first sending unit, configured to send the first text to a text analysis robot model for processing to obtain
And obtaining a classification label of the first text and the classification accuracy of the first text, wherein the analysis robot comprises a preconfigured analysis rule and a text analysis model, the analysis rule is used for outputting the classification accuracy, the text analysis model is obtained by training a neural network model through a preset single text corpus or multiple text corpora, and the classification label is used for describing the intention category of the target client.
7. An electronic device, characterized in that said electronic device comprises a processor and a memory, said memory
Stored with at least one instruction, at least one program, set of instructions to be executed by the processor to implement the method of speech recognition based on intelligent callout and text analysis according to any one of claims 1 to 5.
8. A computer-readable storage medium having stored therein a computer program product
At least one instruction, at least one program, set of instructions to be coded or a set of instructions to be executed by a processor to implement the intelligent callout and text analysis based speech recognition method according to any one of claims 1-5.
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Application publication date: 20220208 |