A method and system for real-time on-screen interpretation of professional terms and complex concepts in live broadcasts

Abstract

This invention relates to a method and system for real-time simultaneous interpretation of technical terms and complex concepts in live streaming, belonging to the field of live streaming interpretation. The method includes: establishing a conceptual potential field for technical terms and complex concepts; during the live stream, real-time acquisition of live audio and cognitive analysis based on the conceptual potential field to obtain the knowledge pressure of each concept; user-side decision-making based on the conceptual potential field and the knowledge pressure to achieve real-time simultaneous interpretation; and self-evolution based on user interaction feedback. This invention is a method for real-time perception of the knowledge pressure of concepts in the live streaming context, dynamic matching of user cognitive frequency, and intelligent selection of interpretation level and related recommendations based on the conceptual potential field.

Description

Technical Field

[0001] This invention belongs to the field of live broadcast interpretation technology, specifically relating to a method and system for real-time simultaneous interpretation of professional terms and complex concepts in live broadcasts. Background Technology

[0002] In current live streaming scenarios, real-time interpretation of technical terms and complex concepts mainly relies on the following methods: First, through manual subtitles or pre-configured keyword dictionaries, pre-set explanatory text is triggered when the host mentions specific words. This method lacks flexibility and real-time performance and cannot adapt to dynamically changing contexts. Second, viewers spontaneously interpret terms through bullet comments or comment sections, but the information quality varies, timeliness is delayed, and it cannot cover the different cognitive levels of all viewers. Third, real-time question-and-answer systems based on natural language processing can return answers based on user-initiated questions, but require active user interaction, interrupting the continuity of viewing, and lack modeling of users' personalized cognitive states. The common shortcomings of existing technologies are: failure to dynamically combine the urgency of concepts in the live streaming context with the user's individual familiarity, resulting in inaccurate interpretation timing (either frequent pop-ups disrupting the viewing experience or missing key interpretations), a one-size-fits-all interpretation depth (unable to provide differentiated content based on users' existing knowledge base), and a lack of utilization of cognitive connections between concepts, making it difficult for users to naturally extend from unfamiliar concepts to related concept networks. Therefore, there is an urgent need for a method that can perceive the knowledge pressure of concepts in the live broadcast context in real time, dynamically match the user's cognitive frequency, and intelligently select the interpretation level and related recommendations based on the concept potential field, so as to improve the efficiency of live broadcast learning and understanding. Summary of the Invention

[0003] To address the aforementioned problems in the existing technology, this invention provides a method and system for real-time simultaneous interpretation of professional terminology and complex concepts during live streaming.

[0004] The objective of this invention can be achieved through the following technical solutions: A method for real-time simultaneous interpretation of technical terms and complex concepts in live streaming, the implementation of which includes the following steps: Step S1: Establish a conceptual potential field for technical terms and complex concepts; Step S2: During the live broadcast, the audio is collected in real time and cognitive analysis is performed based on the conceptual potential field to obtain the knowledge pressure of each concept. ; Step S3: Based on the conceptual potential field and the knowledge pressure Make user-side decisions and enable real-time, screen-sharing interpretation; Step S4: Self-evolution based on user interaction feedback.

[0005] Preferably, the establishment of the conceptual potential field in step S1 specifically involves: Assign inherent potential energy to each of the aforementioned technical terms and complex concepts in the knowledge base. This characterizes the level of sophistication of the technical terms and complex concepts. Assigning cognitive barriers between any two of the aforementioned technical terms and complex concepts. This is used to determine the difficulty of understanding between the two; Preset potential energy values ​​for n interpretation levels ; The conceptual potential field is obtained by: the inherent potential energy of each concept. The cognitive barriers between each pair of concepts The potential energy values ​​of n interpretation levels .

[0006] Preferably, the cognitive analysis in step S2 specifically includes: The live audio is sent to a speech recognition system, which transcribes it into text in real time and extracts all words to form a word set. ; For each concept, obtain its knowledge pressure at the current moment. Mathematically described ,in, Let be the knowledge pressure of concept T at the current time t, representing the urgency with which the concept needs to be interpreted in the current context. Let T be the inherent potential energy of concept T. This is the distance attenuation coefficient. For cognitive distance, when w is a concept in the knowledge base, Otherwise, it is 1. Let w be the cognitive barrier between concept T and word w, where w is a concept in the knowledge base. That is, the inherent potential energy of the word w, otherwise It is 0.

[0007] Preferably, the user-side decision in step S3 specifically includes: For each user u, maintain a cognitive frequency for each concept T. This represents the user's familiarity with the concept, ranging from 0 to 1, indicating the cognitive frequency. The update is as follows: ,in, The cognitive frequency of the previous moment. The time interval from the last update to the current time. The cognitive half-life of user u for concept T. The contribution value for this interaction is calculated if the user clicks, views, or hovers over the interpretation of concept T at the current moment. Otherwise, it is 0; For each user u and each concept T, the resonance coefficients are obtained. Mathematically described ,in, Let T be the inherent potential energy of concept T. The average cognitive frequency of user u across all concepts; when the resonance coefficient If the value exceeds a preset threshold, a pop-up interpretation window will be triggered; otherwise, it will not be triggered. When the pop-up window is triggered for interpretation, the potential energy required for interpretation is obtained. Mathematically described ,in, This is the set of concepts that user u has recently interacted with. The cognitive barrier between concept T and recently interacted concept c. For set The number of elements; based on the potential energy required for the interpretation. The potential energy value that matches the preset interpretation level That is, choose to satisfy The smallest i; If the user clicks the related concept button in the pop-up window, the potential energy gain will be calculated accordingly. Recommending the most profitable related concepts to users, mathematically described as follows: ,in, The cognitive barrier between concept T and related concept R. The inherent potential energy of the related concept R, It is a very small constant.

[0008] Preferably, the self-evolution in step S4 specifically refers to: Record the interval between two consecutive user interactions with the same concept, and adjust the cognitive half-life based on the interval. ; Adjusting cognitive barriers based on user interaction feedback, mathematically described as... ,in, For the updated cognitive barrier. As a current cognitive barrier, To truncate x to the interval [0,1], For learning rate, This refers to the number of users who clicked on the related concept R among those who viewed the interpretation of concept T. To see the total number of users who have viewed the interpretation of concept T, This represents the expected click-through rate.

[0009] A real-time simultaneous interpretation system for professional terms and complex concepts in live streaming, used to execute the aforementioned real-time simultaneous interpretation method for professional terms and complex concepts in live streaming, includes a potential energy field establishment module, a cognitive analysis module, a user-end decision-making module, and a self-evolution module. The potential energy field establishment module is used to establish conceptual potential energy fields for technical terms and complex concepts. The cognitive analysis module is used during the live broadcast to collect live audio in real time and perform cognitive analysis based on the conceptual potential field to obtain the knowledge pressure of each concept. ; The user-side decision module is used to base decisions on the conceptual potential field and the knowledge pressure. Make user-side decisions and enable real-time, screen-sharing interpretation; The self-evolution module is used to perform self-evolution based on user interaction feedback.

[0010] The beneficial effects of this invention are as follows: (1) By establishing a conceptual potential energy field, the system can automatically identify which professional terms in the live broadcast context have high knowledge pressure and then pop up for interpretation at the appropriate time, thus avoiding irrelevant words from frequently triggering and interfering with the audience's experience.

[0011] (2) By maintaining each user’s cognitive frequency and recent interactive concept set, the interpretation level is automatically selected according to the user’s familiarity with different concepts, which improves the relevance of the interpretation content and learning efficiency.

[0012] (3) Through the related concept recommendation mechanism guided by potential energy benefits, users can naturally expand from the currently unfamiliar concepts to related concepts, forming a gradual construction of knowledge network without having to actively search or interrupt the viewing stream.

[0013] (4) By recording user interaction intervals and group click behavior, the cognitive half-life and cognitive barrier are continuously adjusted so that the system can adapt to the memory characteristics and real difficulty of concept association of different user groups, thereby achieving a virtuous cycle of becoming smarter the more it is used. Attached Figure Description

[0014] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0015] Figure 1 This is a flowchart illustrating the steps of a method for real-time simultaneous interpretation of technical terms and complex concepts during live streaming, as proposed by the present invention. Detailed Implementation

[0016] To better understand the invention, various aspects of the invention will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are merely illustrative of exemplary embodiments of the invention and are not intended to limit the scope of the invention in any way. Throughout the specification, the expression "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, the terms "approximately," "about," and similar terms are used as expressions of approximation, not as expressions of degree, and are intended to describe inherent deviations in measured or calculated values ​​that will be recognized by those skilled in the art. Furthermore, the order in which the steps are described in this invention does not necessarily indicate the order in which these steps occur in actual operation, unless otherwise expressly defined or deduced from the context.

[0017] It should also be understood that expressions such as "comprising," "including," "having," "containing," and / or "comprising" are open-ended rather than closed-ended expressions in this specification, indicating the presence of the stated features, elements, and / or components, but not excluding the presence of one or more other features, elements, components, and / or combinations thereof. Furthermore, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features, not just individual elements in the list. Additionally, when describing embodiments of the invention, the word "may" is used to mean "one or more embodiments of the invention." And the term "exemplary" is intended to refer to examples or illustrations.

[0018] Unless otherwise specified, all terms used herein (including engineering and technical terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that, unless expressly stated herein, terms defined in common dictionaries shall be interpreted as having the meaning consistent with their meaning in the context of the relevant art, and not in an idealized or overly formalized sense.

[0019] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other. The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] Example 1: Please see Figure 1 A method for real-time simultaneous interpretation of technical terms and complex concepts during live streaming, including: Step S1: Establish a conceptual potential field for technical terms and complex concepts; Step S2: During the live broadcast, the audio is collected in real time and cognitive analysis is performed based on the conceptual potential field to obtain the knowledge pressure of each concept. ; Step S3: Based on the concept potential field and the knowledge pressure make a decision at the user end to achieve real-time same-screen interpretation; Step S4: Perform self-evolution based on user interaction feedback.

[0021] In this embodiment, the establishment of the concept potential field is specifically as follows: S101: Assign an inherent potential energy to each of the professional terms and complex concepts in the knowledge base , which represents the basic degree of the professional term and the complex concept. The lower the inherent potential energy, the more basic and closer to common sense it is, and an ordinary person can generally understand it without much interpretation; the higher the inherent potential energy, the more specialized and in-depth it is, and the more detailed interpretation is required; S102: Assign a cognitive barrier between any two of the professional terms and complex concepts , which is used to judge the understanding difficulty between the two. The smaller the cognitive barrier, the smaller the cognitive obstacle from understanding the first concept i to understanding the second concept j; S103: Preset the potential energy values of n interpretation levels , for example: the potential energy value corresponding to L1 (a popular interpretation in one sentence) is ; the potential energy value corresponding to L2 (detailed explanation) is ; the potential energy value corresponding to L3 (associated concept network) is ; S104: Obtain the concept potential field, including: the inherent potential energy of each concept ; the cognitive barrier between each pair of concepts ; the potential energy values of n interpretation levels .

[0022] In this embodiment, the cognitive analysis is specifically as follows: S201: Send the live audio into a speech recognition system, transcribe it into text in real time and extract all words (excluding non-concept words such as "le", "de", etc.) to form a word set ; S202: For each concept, obtain its knowledge pressure at the current moment , and the mathematical description is , where is the knowledge pressure of concept T at the current moment t, indicating the urgency of the concept to be interpreted in the current context, is the inherent potential energy of concept T, is the distance attenuation coefficient, which controls the attenuation speed of the pressure of the cognitive distance, is the cognitive distance. When w is a concept in the knowledge base, , otherwise it is 1, Let w be the cognitive barrier between concept T and word w, where w is a concept in the knowledge base. That is, the inherent potential energy of the word w, otherwise It is 0.

[0023] In this embodiment, the user-side decision-making specifically refers to: S301: For each user u, maintain a cognitive frequency for each concept T. This represents the user's familiarity with the concept, ranging from 0 (completely unfamiliar) to 1 (very familiar) (it automatically decays over time and can also be enhanced by user interaction), and the cognitive frequency is... The update is to be performed whenever a user views the interpretation, hovers over, or closes the pop-up: ,in, The cognitive frequency of the previous moment. The time interval from the last update to the current time. Let be the cognitive half-life of user u for concept T, representing the memory retention time. The contribution value for this interaction is calculated if the user clicks, views, or hovers over the interpretation of concept T at the current moment. Otherwise, it is 0; S302: For each user u and each concept T, obtain the resonance coefficients. The higher the value, the more the user should be prompted to interpret the concept T. Mathematically, this is described as follows: ,in, Let T be the inherent potential energy of concept T. The average cognitive frequency of user u across all concepts; when the resonance coefficient If the value exceeds a preset threshold, a pop-up interpretation window will be triggered; otherwise, it will not be triggered. S303: When the pop-up window is triggered for decoding, the potential energy required for decoding is obtained. The larger the value, the more detailed the interpretation required; mathematically, it is described as follows: ,in, This is the set of concepts that user u has recently interacted with. The cognitive barrier between concept T and recently interacted concept c. For set The number of elements; based on the potential energy required for the interpretation. The potential energy value that matches the preset interpretation level That is, choose to satisfy The smallest i, for example, If the value is 0.2, which is less than 0.3, then choose L1 (in short). S304: If the user clicks the related concept button in the pop-up window (or multiple related concepts are directly displayed for selection in L3), then based on the potential energy gain... Recommending the most profitable related concepts to users, mathematically described as follows: ,in, The cognitive barrier between concept T and related concept R. The inherent potential energy of the related concept R, It is a very small constant.

[0024] In this embodiment, the self-evolution specifically refers to: S401: Record the interval between two consecutive interactions of a user with the same concept, and adjust the cognitive half-life based on the interval. For example, shortening the cognitive half-life when the interval is less than a certain threshold. ; S402: Adjusting cognitive barriers based on user interaction feedback, mathematically described as follows: ,in, For the updated cognitive barrier. As a current cognitive barrier, To truncate x to the interval [0,1], For learning rate, This refers to the number of users who clicked on the related concept R among those who viewed the interpretation of concept T. To see the total number of users who have viewed the interpretation of concept T, The expected click-through rate. That is, after users view the interpretation of T, what percentage of users subsequently click on the related concept R? If this percentage is higher than the expected percentage based on the current cognitive barrier, it means that the actual cognitive barrier from T to R is smaller than estimated, and the cognitive barrier should be lowered; if the percentage is lower than expected, the cognitive barrier should be raised.

[0025] Example 2: A real-time simultaneous interpretation system for professional terms and complex concepts in live streaming includes a potential energy field establishment module, a cognitive analysis module, a user-end decision-making module, and a self-evolution module; The potential energy field establishment module is used to establish conceptual potential energy fields for technical terms and complex concepts. The cognitive analysis module is used during the live broadcast to collect live audio in real time and perform cognitive analysis based on the conceptual potential field to obtain the knowledge pressure of each concept. ; The user-side decision module is used to base decisions on the conceptual potential field and the knowledge pressure. Make user-side decisions and enable real-time, screen-sharing interpretation; The self-evolution module is used to perform self-evolution based on user interaction feedback.

[0026] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for real-time simultaneous interpretation of technical terms and complex concepts during live streaming, characterized in that, Includes the following steps: Step S1: Establish a conceptual potential field for technical terms and complex concepts; Step S2: During the live broadcast, the audio is collected in real time and cognitive analysis is performed based on the conceptual potential field to obtain the knowledge pressure of each concept. ; Step S3: Based on the conceptual potential field and the knowledge pressure Make user-side decisions and enable real-time, screen-sharing interpretation; Step S4: Self-evolution based on user interaction feedback.

2. The method for real-time simultaneous interpretation of professional terminology and complex concepts in live streaming according to claim 1, characterized in that, The establishment of the conceptual potential field in step S1 is specifically as follows: Assign inherent potential energy to each of the aforementioned technical terms and complex concepts in the knowledge base. This characterizes the level of sophistication of the technical terms and complex concepts. Assigning cognitive barriers between any two of the aforementioned technical terms and complex concepts. This is used to determine the difficulty of understanding between the two; Preset potential energy values ​​for n interpretation levels ; The conceptual potential field is obtained by: the inherent potential energy of each concept. The cognitive barriers between each pair of concepts The potential energy values ​​of n interpretation levels .

3. The method for real-time simultaneous interpretation of professional terminology and complex concepts in live streaming according to claim 1, characterized in that, The cognitive analysis in step S2 specifically refers to: The live audio is sent to a speech recognition system, which transcribes it into text in real time and extracts all words to form a word set. ; For each concept, obtain its knowledge pressure at the current moment. Mathematically described ,in, Let be the knowledge pressure of concept T at the current time t, representing the urgency with which the concept needs to be interpreted in the current context. Let T be the inherent potential energy of concept T. This is the distance attenuation coefficient. For cognitive distance, when w is a concept in the knowledge base, Otherwise, it is 1. Let w be the cognitive barrier between concept T and word w, where w is a concept in the knowledge base. That is, the inherent potential energy of the word w, otherwise It is 0.

4. The method for real-time simultaneous interpretation of professional terminology and complex concepts in live streaming according to claim 1, characterized in that, The user-side decision in step S3 specifically refers to: For each user u, maintain a cognitive frequency for each concept T. This represents the user's familiarity with the concept, ranging from 0 to 1, indicating the cognitive frequency. The update is as follows: ,in, The cognitive frequency of the previous moment. The time interval from the last update to the current time. The cognitive half-life of user u for concept T. The contribution value for this interaction is calculated if the user clicks, views, or hovers over the interpretation of concept T at the current moment. Otherwise, it is 0; For each user u and each concept T, the resonance coefficients are obtained. Mathematically described ,in, Let T be the inherent potential energy of concept T. The average cognitive frequency of user u across all concepts; when the resonance coefficient If the value exceeds a preset threshold, a pop-up interpretation window will be triggered; otherwise, it will not be triggered. When the pop-up window is triggered for interpretation, the potential energy required for interpretation is obtained. Mathematically described ,in, The set of concepts that user u has recently interacted with. The cognitive barrier between concept T and recently interacted concept c. For set The number of elements; based on the potential energy required for the interpretation. The potential energy value that matches the preset interpretation level That is, choose to satisfy The smallest i; If the user clicks the "Related Concepts" button in the pop-up window, the potential return will be calculated based on the potential energy. Recommending the most profitable related concepts to users, mathematically described as follows: ,in, The cognitive barrier between concept T and related concept R. The inherent potential energy of the related concept R, It is a very small constant.

5. The method for real-time simultaneous interpretation of professional terminology and complex concepts in live streaming according to claim 1, characterized in that, The self-evolution mentioned in step S4 specifically refers to: Record the interval between two consecutive user interactions with the same concept, and adjust the cognitive half-life based on the interval. ; Adjusting cognitive barriers based on user interaction feedback, mathematically described as... ,in, For the updated cognitive barrier. As a current cognitive barrier, To truncate x to the interval [0,1], For learning rate, This refers to the number of users who clicked on the related concept R among those who viewed the interpretation of concept T. To see the total number of users who have viewed the interpretation of concept T, This represents the expected click-through rate.

6. A system for real-time simultaneous interpretation of technical terms and complex concepts during live streaming, characterized in that, The system is applied to the real-time simultaneous interpretation method of professional terms and complex concepts in live broadcasts as described in any one of claims 1-5, including a potential energy field establishment module, a cognitive analysis module, a user-end decision-making module, and a self-evolution module; The potential energy field establishment module is used to establish conceptual potential energy fields for technical terms and complex concepts. The cognitive analysis module is used during the live broadcast to collect live audio in real time and perform cognitive analysis based on the conceptual potential field to obtain the knowledge pressure of each concept. ; The user-side decision module is used to base decisions on the conceptual potential field and the knowledge pressure. Make user-side decisions and enable real-time, screen-sharing interpretation; The self-evolution module is used to perform self-evolution based on user interaction feedback.

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