17 results about "Correct response" patented technology

In the present invention, a smartphone is provided with an answerphone function for carrying out an automatic conversation with a caller if there is an unattended incoming call. A main control unit of the smartphone generates speech text by converting the speech of the caller into text, and collects, from schedule information and on the basis of the speech text, schedules for creating an input sentence. The main control unit inputs the input sentence created on the basis of the speech text and the collected schedules to a generative AI server so as to cause the generative AI server to create response text. The main control unit corrects the response text at a disclosure granularity corresponding to the identity of the caller, creates response speech by converting the corrected response text back into speech, andl carries out an automatic conversation with the caller by using the response speech.

The invention discloses a dynamic key encryption communication method in a monitoring system, and the method comprises the steps: S1, generating a random dynamic key and a convolution matrix after monitoring equipment is started; s2, the monitoring equipment initiates a connection establishment request, encrypts the serial number SN of the monitoring equipment and the authentication key through the master key, and sends the serial number SN and the authentication key to the server; s3, the server side verifies the serial number SN and the authentication key of the monitoring equipment, if the key is correct, a correct response is returned, and otherwise, a wrong response is returned; s4, if the monitoring equipment receives the correct response, the monitoring equipment sends the dynamic key generation method and the dynamic key initial value to the server side together, and the server side replies the response to the monitoring equipment after receiving the command; and S5, then the monitoring equipment and the server side communicate according to the agreed dynamic key, and the key needs to be regenerated every time the request response is completed, the key is hidden in the form of the dynamic key, so that the security of information interaction is ensured, the number of encryption rounds can be reduced, and the encryption and decryption efficiency is improved.

The invention relates to a customer service response correction method and device, equipment and medium in the technical field of e-commerce, and the method comprises the steps: carrying out the preprocessing of each manual customer service session in a manual customer service session set, and obtaining a target session set; adopting a large language model to determine each standard consultation text describing a corresponding user consultation intention in the target session set; when customer service knowledge materials related to the standard consultation text exist in a preset customer service knowledge base, all the customer service knowledge materials are recalled and used for generating a corresponding to-be-evaluated response text; and when the answer assessment text of the to-be-assessed response text represents an answer error, executing a corresponding repair process according to an error reason in the answer assessment text so as to regenerate a corresponding correct response text after repair. According to the invention, response defects can be accurately repaired, so that high-quality intelligent customer service is provided.

The embodiment of the invention provides a dialogue information processing method and device, equipment and a storage medium. The method includes: in a conversational page, receiving a first set of text units from a language model, the first set of text units being included in a first portion of a response of the language model, the response being a text stream generated by the language model in a streaming manner based on cues; according to the received time sequence of each text unit in the first group of text units, presenting a current response for the cue word; and processing the current response based on syntax check data, the syntax check data indicating a syntax error in the current response. In this way, it can be determined whether a syntax error exists in the received text stream, and in the event that the syntax error exists, the response is processed to obtain a correct response. Therefore, the response accuracy can be improved.

The present disclosure relates to systems and methods for generating contextually, grammatically, and conversationally correct answers to input questions. Embodiments provide for linguistic and syntactic structure analysis of a submitted question in order to determine whether the submitted question may be answered by at least one headnote. The question is then further analyzed to determine more details about the intent and context of the question. A federated search process, based on the linguistic and syntactic structure analysis, and the additional analysis of the question is used to identify candidate question-answer pairs from a corpus of previously created headnotes. Machine learning models are used to analyze the candidate question-answer pairs, additional rules are applied to rank the candidate answers, and dynamic thresholds are applied to identify the best potential answers to provide to a user as a response to the submitted question.

A method and system for supra-threshold vision testing. The method includes (a) selecting an object having a uniquely identifiable configuration at each of a plurality of successive rotational orientations, (b) presenting to a person the object in one of the rotational orientations, (c) receiving from the person a response identifying the perceived rotational orientation, (d) measuring a response time and correctness of the response, (e) repeating the steps (b)-(d) a predetermined number of times, and (f) determining a metric value using the number of correct responses and the measured response times from steps (b)-(d) according to a predetermined formula, wherein the test is performed under supra- threshold conditions.

Systems and methods are disclosed for protecting data. A device requesting access to the data is required to correctly respond to a challenge embedded in the data provided responsive to a request for the data. If the device that receives the data is able to generate the correct response to the challenge, the device can be validated as the device that was intended to receive the data. When the device is able to generate the correct response to the challenge, the correct response can indicate that the requested data is being used as intended. That is, the challenge can ensure that the context specified in the request, which was deemed an appropriate environment for use of the data by the server that triggered distribution of the data responsive to the request, is, in fact, the context in which the data is actually going to be used.

A method in a computing system to facilitate a multi-player game by selecting a group of computing devices operated by respective users, distributing interactive content that includes one or more questions with a set of selectable answers to the group of computing devices, receiving a response to the one or more questions, determining a score based on whether the response is a correct response and a number of computing devices in the group from which the correct response was received, determining a respective ranking based at least on the corresponding score, and providing the respective ranking to each computing device in the group.

The invention discloses a control stability test method and system suitable for a special transformer terminal, and the method comprises the steps: transmitting a switching-on or switching-off instruction to a tested terminal at regular time in a test period, and recording the instruction transmission frequency and the correct response frequency of a circuit breaker; simulating a dynamic test working condition through a random selection mode based on a plurality of predefined working conditions and weights thereof; and calculating a control stability index of the special transformer terminal according to the instruction sending times and the correct response times. Through the technical scheme of combining timing instruction testing, weight-based dynamic working condition simulation and stability index calculation, the control reliability of the terminal under dynamic interference can be automatically and comprehensively tested, and the testing safety and efficiency are remarkably improved, so that the technical effect of ensuring power utilization safety is achieved. And moreover, the limitation that the test can only be carried out under ideal conditions in the prior art is effectively overcome, so that the test result can more truly reflect the special transformer, and the comprehensiveness and authenticity of the test are improved.

The invention provides an RAG-based question and answer system optimization method and device, and the method comprises the steps: firstly grouping a test set, then determining a first evaluation label for each test sample in a non-related domain group, and determining a second evaluation label for each test sample in a related domain group; the first evaluation tag is a correct response tag or a cue word optimization tag, and the second evaluation tag comprises at least one of a correct response tag, a correct recall tag, a cue word optimization tag, a recall optimization tag, an information fusion optimization tag and a corpus lacking tag; therefore, the response accuracy rate and the recall accuracy rate can be respectively calculated based on the number of the test samples, the number of the correct response labels and the number of the correct recall labels. In this way, when the evaluation is completed, the test samples carrying the cue word optimization labels, the recall optimization labels or the corpus lacking labels can also enable research and development personnel to clearly know the reason for low response quality, and therefore optimization is conducted in a targeted mode.

The present disclosure provides a data generation method, relates to the technical field of artificial intelligence, and particularly relates to the technical field of large models and agents. A specific implementation scheme is as follows: at least one to-be-evaluated response result is generated by using at least one of a plurality of data synthesis expert units; at least one evaluation result for the at least one to-be-evaluated response result is determined by using at least one of the plurality of data synthesis expert units; in response to determining that the at least one evaluation result indicates that there is at least one to-be-corrected response result in the at least one to-be-evaluated response result, at least one correction data for at least one data synthesis expert unit is determined according to the at least one evaluation result for the at least one to-be-corrected response result; and the operation of generating the at least one to-be-evaluated response result by using at least one of the plurality of data synthesis expert units is returned to. The present disclosure also provides a model training method, a data processing method, a device, an electronic device and a storage medium.

The application discloses a vehicle control method and a vehicle, and relates to the technical field of vehicle control, and comprises the following steps: in response to a slip detection result of a vehicle, determining a slip level of the vehicle and a driver psychological load level; realizing multi-source data fusion judgment of the vehicle state and the driver state. Based on the slip level of the vehicle, a guide speech for the driver of the vehicle is determined; the driver can be provided with specific operation instructions, and the driver can be prevented from being at a loss or making a misoperation due to ambiguous prompts. Based on the driver psychological load level of the vehicle, an output mode of the guide speech is determined; the guide presentation form can be adaptively adjusted according to the psychological state of the driver. The guide speech for the driver of the vehicle is output by using the output mode of the guide speech. The application is beneficial to giving accurate guide speech as soon as possible in the case of vehicle slip, so that the driver of the vehicle can make correct response measures as soon as possible, and the operation guide effect of vehicle slip is improved.

This invention provides a text processing method, a human-computer interaction method, a device, and a storage medium. The method includes: acquiring text to be processed; determining the corresponding prompt vector and prompt text for the text to be processed; and finally, inputting the text to be processed and its corresponding prompt vector and prompt text into a question-answering model so that the question-answering model outputs the correct response text. As the names suggest, the prompt vector is the prompt information in vector form, and the prompt text is the prompt information in text form. Using the above method, on the one hand, the vector prompts can serve as supplementary parameters for the question-answering model to improve the accuracy of the response text generated by the question-answering model; on the other hand, the text prompts can serve as supplementary background knowledge for the text to be processed, enabling the question-answering model to generate response text more accurately based on more background knowledge. That is, using different forms of prompt information can supplement the question-answering model from different perspectives to improve the accuracy of the response text generated by the question-answering model.

This invention relates to artificial intelligence dialogue system technology, providing a dialogue generation method, apparatus, electronic device, and computer storage medium. The method includes: acquiring the response content output by a preset dialogue model in response to a user dialogue; if the response content is inconsistent with preset character traits, determining a deviation dimension, wherein the preset character traits describe the role identity attribute information of the virtual character set by the preset dialogue model; correcting the response content according to the deviation dimension; and generating a character dialogue based on the user dialogue and the corrected response content. This invention can make the correction more targeted by correcting the response content according to the deviation dimension, achieving consistent dialogue and preventing style drift.

A data processing system implements accessing a datastore of training data using a model training unit to obtain a first training sample, the first training sample comprising a first natural language utterance, first ground truth information, the first natural language utterance requesting that content be generated by a language model, the first ground truth information providing a first example of first expected output of the language model in response to the first natural language utterance; constructing a first prompt based on the first natural language utterance using a prompt construction unit; providing, using the prompt construction unit, the first prompt to the language model as an input to cause the language model to generate a first output; analyzing the first output and the first ground truth information using the model training unit to determine whether the first output is erroneous; constructing, using the prompt construction unit, a second prompt that instructs the language model to generate a first self-reflection response that indicates why the language model generated the first output; providing the second prompt as an input to the language model to cause the language model to generate the first self-reflection response; constructing, using the prompt construction unit, a third prompt that includes the first self-reflection response, the third prompt instructing the language model to generate prompt improvement instructions to be included in subsequently constructed prompts for the language model to assist the language model in generating a correct response to the subsequently constructed prompts; providing the third prompt to the language model to cause the language model to generate the prompt improvement instructions; and including the prompt improvement instructions in the subsequently constructed prompts generated using the prompt construction unit.

A method and system for dynamically generating custom location-related queries for authentication and access management. The embodiments provide a system that authenticates users of secured resources regulated by computing device such as ATM and payment terminals by requiring a correct response to a question about the user's recent location activity. Where the system determines the user has provided the correct response, a verification signal approving the request is transmitted from the system to the access management system regulating access to the secured resource, causing the processing of a payment or release funds, or otherwise grant access to the desired secured resource.

The invention discloses a reinforcement learning method and device for a large model. In the method, a user question is input into a to-be-trained large model, multiple responses and confidence coefficients corresponding to the responses are obtained, and correctness rewards of the responses are determined according to correct answers of the user question. And for any response, performing weighting operation and cutting operation based on the confidence coefficient of the response and the correctness reward of the response to obtain the reward of the response. Wherein the weighting operation is used for using the reward of the high-confidence correct response greater than the reward of the low-confidence correct response, and the reward of the high-confidence error response is less than the reward of the low-confidence error response. The cutting operation is used for taking the lower bound value as the award when the award of the correct response is lower than the lower bound value and taking the upper bound value as the award when the award of the error response is higher than the upper bound value. Next, a model update based on a reinforcement learning algorithm is performed according to the plurality of responded rewards to update the large model. Privacy protection needs to be performed on training data used in the training process.