19 results about "Interview methods" patented technology

The invention provides an assessment interview method and device for enterprise employees and a storage medium, and the method comprises the steps: determining an initial problem in a preset assessment interview problem library based on the post type and historical performance data of the enterprise employees; questioning by using the initial question so as to receive answer information of the enterprise employees; determining the semantic integrity of the answer information; if the semantic integrity is smaller than a preset integrity threshold value, generating a question-chasing question of the initial question according to a semantic element type missing in the answer information; asking questions by utilizing the question-asking questions to receive supplementary answer information of the enterprise employees; and according to the answer information, supplementing the answer information, and determining an assessment interview evaluation result of the enterprise employees. According to the method and the device, the questioning content can be adjusted according to the post types and the historical performance data of the enterprise employees, and the questioning can be selectively performed according to the answer information of the enterprise employees, so that the questioning of the assessment interviews is more accurate and deep, and the accuracy of the result obtained by the assessment interviews is improved.

The invention provides a simulation interview method and device based on a large model, electronic equipment, a storage medium and a computer program product, relates to the technical field of artificial intelligence, in particular to the technical fields of large models, natural language understanding, simulation interview and the like, and can be applied to simulation interview scenes. According to the specific implementation scheme, through an artificial intelligence large model, an interview question for an interview object is generated according to historical question and answer data of the interview object in the interview process; obtaining response data of the interview object to the interview question; and determining the response quality of the interview object to the interview question according to the response data through an artificial intelligence large model. According to the invention, the logicality of interview problems in the interview process is improved, and the interactivity between the interview process and the user is simulated; the response quality is immediately determined according to the response data of the interview question, and the simulation interview requirement of the interview object is met.

This invention relates to the field of artificial intelligence interview system technology, specifically to an integrated AI interview method and system based on interpretable deep assessment. The method includes: collecting and simultaneously preprocessing the interviewee's audio and video data using an integrated device; analyzing non-verbal behavioral features and speech semantic content features using a multimodal deep learning model; inputting the extracted multimodal features into an attention-based interpretable fusion assessment model for deep correlation and weighted calculation to generate an assessment of non-cognitive abilities; and finally outputting a structured assessment report including a comprehensive score, multidimensional analysis, and citations of key evidence fragments. This invention, through deep multimodal fusion and interpretability technology, achieves an objective and in-depth assessment of candidates' soft skills, and makes the assessment results transparent and traceable, effectively improving the accuracy, credibility, and practical value of AI interviews.

The invention provides a self-adaptive AI interview method and device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence, in the method, the next operation (namely rule instructions, or strategy optimization behaviors, specifically next interview questions, or interview termination) can be dynamically adjusted according to interview answers, the dynamic adaptability is good, the method is more flexible, and in addition, the method can be applied to the field of AI interview. In the comprehensive scoring process, a mixed scoring strategy is adopted, the method is more scientific, when the current state does not meet the trigger condition in the preset rule, the offline reinforcement learning agent is adopted to make an intelligent decision on the current state, then the strategy optimization behavior is obtained, the accuracy is better, in addition, the preset rule is pre-configured, the controllability is good, and the user experience is improved. And the offline reinforcement learning agent is a conservative Q learning algorithm, and during training, Q value overestimation of behaviors outside distribution of a training data set can be inhibited through a conservative regularization item, so that non-compliant behaviors can be inhibited, namely, the behaviors are more controllable and compliant.

The application relates to the technical field of artificial intelligence and psychological interviews, in particular to an emotional conversation intelligent interview method and system, which comprises the following steps: collecting voice, text and micro-expression features through a multi-modal sensing unit; constructing a semantic-emotion coupling feature model, monitoring the mapping relationship between semantic logic and emotional fluctuation and calculating a conflict coefficient; when the semantic feedback and the emotional valence are negatively correlated, triggering a contradiction seeking logic; using a heterogeneous graph converter to construct interview multi-dimensional features into a heterogeneous graph, generating a context vector through an attention mechanism; generating a guiding prompt word with an emotional regulation factor based on the vector, guiding the interviewee to release real psychological motivation. The application can accurately identify the real intention hidden under the disguise, eliminate individual expression differences, balance deep mining and empathy injection, and realize self-adaptive and high-precision collection of interview information.

The invention discloses an intelligent interview method and device, and a storage medium, and relates to the technical field of interview evaluation, and the method comprises the steps: carrying out the question screening analysis of a target post question bank based on an interview resume, target post recruitment information, and a plurality of target assessment dimensions, obtaining target assessment questions corresponding to each target assessment dimension of an interviewer, and obtaining the target assessment questions corresponding to each target assessment dimension; and each target evaluation standard. Receiving answer voices of the interviewer for each target assessment question, aggregating the answer voices under the same target assessment dimension through a capability assessment large model, and determining a target answer voice text in each target assessment dimension; and performing interview assessment analysis on the corresponding target answer voice text by using each target assessment standard through the ability assessment large model to obtain each target first score, and determining the interview score of the interviewer, thereby solving the technical problem of ability misjudgment of the interviewer caused by strong subjectivity of interview assessment in traditional interviews, and improving the interview experience of the interviewer. And the interview evaluation efficiency and fairness are improved.

The invention relates to the technical field of computer science, in particular to an artificial intelligence investigation and deep interview system, which is characterized by comprising a basic unit, an algorithm and model unit, a function unit, an application unit and a safety protection unit, the basic unit is used for bearing core tasks of computing power, algorithms and data and preparing data for an investigation and interview system; the algorithm and model unit is responsible for understanding and processing human languages, learning question and answer rules and interview strategies through training, and identifying and analyzing emotional changes of users in interviews; the function unit is used for generating questionnaires, collecting generated data and analyzing and processing the data; through integration of basic support, an algorithm model, function application, result display and safety protection, advanced natural language processing and machine learning technologies are utilized, questionnaires are automatically generated, data are analyzed in real time, user privacy is protected, and efficient and accurate investigation interview experience is provided.

The application relates to the field of intelligent interviews, and discloses an intelligent interview method and device based on a large language model, equipment and a storage medium, which are used for fusing a large language model to realize intelligent and accurate interviews. The method comprises the following steps: acquiring post descriptions and candidate resume information, generating a dynamic post portrait and an interview cognitive graph; relying on a pre-trained first large language model, combining a current state of the cognitive graph to determine a deep exploration strategy and a current deep evaluation target; generating interactive content through a pre-trained second large language model, receiving candidate text, acoustic and visual multi-modal response information; analyzing the multi-modal response to obtain corresponding features, and updating the interview cognitive graph; judging whether a cognitive convergence threshold is reached, recursively asking questions if the threshold is not reached, and promoting the interview or ending the interview if the threshold is reached; after the interview is ended, generating a main evaluation conclusion based on a final cognitive graph, questioning and debating through a pre-trained third large language model, and generating a comprehensive evaluation report containing core arguments of the pro and con sides.

The invention relates to the technical field of artificial intelligence, and discloses an AI interview method, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining an interview text; determining a first speech speed and a first pause frequency of the candidate according to the interview text; the first pause frequency is used for describing the pause frequency in the process that the candidate inputs the interview audio corresponding to the interview text; determining the semantic integrity probability of the interview text; determining the probability that the candidate does not continue speaking according to the first speech speed, the first pause frequency and the semantic integrity probability; and determining whether to continuously ask questions according to the probability that the candidates do not continuously speak. Therefore, the opportunity of continuing to ask questions by the AI interviewer can be adaptively adjusted according to the speaking style of the candidate, so that the AI interviewer takes over a conversation at a reasonable opportunity, and the interview experience feeling of the candidate is improved.

The invention discloses an interview data encryption protection method and system and an interview method for examination tutoring, and relates to the field of data encryption, high verification accuracy is achieved on a data set through facial feature extraction based on an ArcFace model, and the side face recognition error rate is greatly reduced through a dynamic posture correction algorithm; in combination with the biological facial features, accurate identity verification operation is performed on the interviewer before interview, so that the data security in the interview is effectively ensured; through framing parameter dynamic adjustment and frequency band energy control, a signal-to-noise ratio difference value is ensured to be within a preset range, and the audio safety of interviewers in the interview process is ensured; in addition, the audio is fragmented, so that single-node cracking needs a large amount of operation, the safety of interview data storage is greatly improved, meanwhile, the data fragments are stored across multiple geographic nodes, and the data availability is high when a single region has a fault.

The invention discloses an intelligent simulation interview method and device, computer equipment and a storage medium. The method comprises the steps that voice data of a virtual interviewer and voice data of a job seeker are collected, speaker separation is carried out, and first text data corresponding to the virtual interviewer and second text data corresponding to the job seeker are obtained; performing intention recognition and question classification on the first text data, and distinguishing technical questions from non-technical questions; if the question type of the technical question is a structured question, retrieving a knowledge graph to return a reference answer with a code example, and if the question type of the technical question is an open question, calling a large language model to generate a reference answer conforming to an STAR principle; and returning the reference answer and an interview performance evaluation report generated based on the second text data of the job seeker to the client. According to the invention, a plurality of links such as voice acquisition, speaker separation, intention recognition, question classification, multi-channel answer generation and real-time display are combined, a closed-loop intelligent interview simulation system is constructed, and the sense of reality of simulation interview is improved.

This application relates to the field of artificial intelligence technology, disclosing an AI interview method, electronic device, storage medium, and program product. The method includes: acquiring interview text; determining the candidate's first speaking speed and first pause frequency based on the interview text; the first pause frequency describing the number of pauses during the candidate's input of the interview audio corresponding to the interview text; determining the semantic integrity probability of the interview text; determining the probability that the candidate will not continue speaking based on the first speaking speed, the first pause frequency, and the semantic integrity probability; and determining whether to continue asking questions based on the probability that the candidate will not continue speaking. This allows the AI ​​interviewer to adaptively adjust the timing of continuing to ask questions according to the candidate's speaking style, enabling the AI ​​interviewer to take over the conversation at an appropriate time, thereby improving the candidate's interview experience.

The invention relates to the technical field of talent evaluation, in particular to a school recruitment talent evaluation system and method based on an immersive training camp and a multi-dimensional portrait, and the system comprises a precise interview preliminary screening module which is used for carrying out the preliminary screening of candidates through a behavior interview method, and an immersive training camp management module which is configured to simulate a real working scene, the method comprises the following steps: organizing candidates to participate in a training task for several days, a multi-dimensional behavior data acquisition module for recording behavior indexes of the candidates in training in real time, including speaking duration, collaborative proposal times and emotional stability data, a talent portrait generation module, analyzing the behavior data based on an algorithm model, and a decision support module, according to the school recruitment talent evaluation system and method based on the immersive training camp and the multi-dimensional portrait, a two-stage evaluation mechanism is adopted, candidates are rapidly screened through a behavior interview method, and then the comprehensive ability of the candidates is observed by simulating the training camp depth of a real working scene.

The invention discloses an AI interview method and system based on a multi-modal large model. The method comprises the steps that 1, an interview problem is automatically generated through a problem generation module; 2, in the process that the user answers the question, recording the voice and video of the user through an interview recording module, and sending the voice and video to an answer analysis module; 3, an answer analysis module analyzes the answer of the user to the interview question, and quantitatively scores the question answer condition of the user based on the scoring dimension; step 4, performing comprehensive analysis on the interview process by a scoring and questioning generation module, and generating questioning questions; and 5, performing comprehensive score calculation according to all questions answered by the user, generating an interview report, and sending the interview report to the HR. The invention relates to the technical field of artificial intelligence, and can solve the existing technical problems.

The invention discloses an intelligent interview method and device, a medium and a program product, and relates to the field of artificial intelligence. The intelligent interview method comprises the steps of obtaining research and development interview demand data; according to the research and development interview demand data, screening target interview entries from the research and development interview knowledge base; and after the interviewer passes the test of the test problem corresponding to the target interview entry, updating the interview entry in the research and development interview knowledge base according to the interview reply data of the interviewer and the project research and development information after the interviewer enters the job. According to the technical scheme provided by the embodiment of the invention, intelligent interview can be carried out on the interviewer according to actual work needs, and the interviewer is assisted in screening out the interviewer competent for work.

The application discloses an interview method and device based on a video interview system, relates to the technical field of artificial intelligence, and mainly aims at reducing the possibility of artificial review of interview results and improving interview efficiency. The main technical scheme of the application is as follows: obtaining recruitment requirements of a target post, resume information of a candidate and a post evaluation result; generating a current interview question based on a capability item of the recruitment requirements and asking the candidate the question so as to collect, through a video interaction collection module, the answer content of the candidate to the current interview question and facial emotional information when the candidate answers; determining the effectiveness of the current answer according to the answer content and the facial emotional information; determining a target question determination strategy in a question follow-up strategy and a question promotion strategy according to whether the answer effectiveness meets preset effectiveness requirements, and determining a next interview question according to the target question determination strategy until a preset question asking deadline requirement is met; and generating an interview result based on all the interview questions, the answer content and the answer effectiveness.

The application provides an interview method and device, and a computer readable storage medium. The interview method comprises the following steps: asking a candidate a plurality of questions according to a plurality of competencies required by a job position; collecting answer texts of the candidate answering each question, and forming a question and answer pair for each answer text and the question text corresponding thereto; segmenting the question text and the answer text of each question and answer pair to obtain a plurality of question sentences and a plurality of answer sentences for each question and answer pair; and using a pre-trained reasoning model to perform information interaction, semantic reasoning and result classification on the plurality of question sentences and the plurality of answer sentences of each question and answer pair to obtain a comprehensive score result of the candidate for the plurality of competencies.

The invention provides an AI-based multi-modal fusion recruitment interview method and device and a medium, and belongs to the technical field of artificial intelligence. The AI-based multi-modal fusion recruitment interview method comprises the following steps: acquiring multi-modal data of an interviewer by using a plurality of sensors; according to a multi-modal feature extraction algorithm corresponding to the data type of the multi-modal data, extracting a corresponding multi-modal feature from the multi-modal data; according to a score weight optimization algorithm based on reinforcement learning, the score weight of the multi-modal features is adjusted in real time, the score weight is fused with the multi-modal features, and a dynamic score of the interviewer is obtained; performing prejudice removal processing on the personal information of the interviewer by using a prejudice removal algorithm to obtain a prejudice removal processing result; and integrating the dynamic score and the prejudice removal processing result by adopting an edge calculation mode, and generating an interview evaluation report of the interviewer. According to the invention, the problems of insufficient multi-modal analysis capability, algorithm prejudice and high real-time interaction delay in the prior art can be solved.

Embodiments of the present application disclose a remote interview method and device, electronic equipment and storage medium; can respond to the interview request of the interviewee, determine the temporary extension number of the interview service personnel of the target interview order, establish the video call connection of the interviewee and the interview service personnel based on the temporary extension number, when the interviewee and the interview service personnel carry out video call, according to the video call information in the video call process, the interview compliance identification result of the interviewee and the interview service personnel is obtained by carrying out interview compliance identification, record the video call information, if the interview compliance identification result is interview compliance, keep the video call connection, respond to the call disconnect operation of the interviewee and / or the interview service personnel, disconnect the video call connection, trigger the order processing system to carry out subsequent processing for the target interview order based on the video call information; can improve the efficiency of the interview on the basis of guaranteeing the compliance of the interview process, reduce the cost of the interview.