248 results about "Spoken dialog" patented technology

The invention discloses a voice interaction optimization method and system based on a multi-modal large model, and relates to the technical field of artificial intelligence and voice interaction, and the method comprises the steps: carrying out the voice recognition in response to the real-time voice of a user, and obtaining voice text information; according to the voice text information, combining the voice waveform of the real-time voice of the user as the input of a multi-modal recognition model, so as to judge whether the voice dialogue is interrupted and recognize the interruption intention, and obtaining a voice interruption result; obtaining a new intention of the user according to a voice interruption result, and dynamically adjusting a system response strategy to realize interaction optimization; the accuracy and comprehensiveness of interruption detection are improved through multi-modal fusion, so that the interruption intention is accurately recognized to respond to the user intention in real time, the system dialogue interaction efficiency and reliability are remarkably improved, and the defects that existing voice interruption detection is not high in detection accuracy, dynamic response of user interruption behaviors cannot be achieved, and user experience is poor are overcome. Therefore, the problems of low interaction efficiency and poor reliability of the voice dialogue system are solved.

The invention discloses an accurate international communication digital human real-time dialogue method fused with a multi-modal technology. The method comprises the following steps: S1, constructing a digital human image and tone; s2, propagation content generation and problem guidance; s3, semantic analysis and intention clarification based on the real-time voice dialogue; s4, geographic preference modeling and path planning; s5, cross-context propagation content generated based on retrieval enhancement is generated; s6, visually displaying the propagation content; and S7, carrying out digital human-driven multi-language propagation content real-time output and feedback closed-loop optimization. Through accurate utterance expression analysis, accurate international propagation problem recommendation is provided, cross-context propagation content generation based on semantic understanding is realized, digital people with voice features and visual images are constructed, real-time dialogue interaction of users is realized, and user experience is improved. The system can carry out geographic modeling according to the region where the accurate problem is located, language preference and propagation object culture characteristics, and differential propagation path planning is achieved.

The embodiment of the invention provides a voice conversation method and system, electronic equipment, a storage medium and a program product. One method is implemented as follows: a voice dialogue stream (which can be an inquiry voice stream input by a user for a target commodity) of a user is subjected to streaming response, a plurality of dialogue text segments are generated in a segmented manner in the streaming response process, and the dialogue text segments are output in real time after being generated and stored in a first cache queue; and when it is detected that the reply text fragment is stored in the first cache queue, the stored reply text fragment is converted into a reply voice fragment in real time and played. The streaming response may be performed by an agent. Visibly, according to the response of the voice dialogue stream of the user, the dialogue is played while being generated, the waiting time from text to voice synthesis can be greatly shortened, and therefore the response time can be shortened.

The invention relates to the technical field of voice dialogues, and discloses a robot dialogue intelligent early warning system based on voice outbound, which comprises a voice recognition module for receiving a voice signal in a real-time call initiated by an outbound robot and converting the voice signal into a dialogue text; the intention analysis module is used for extracting semantic features and emotional features from the dialogue text, inputting the semantic features and the emotional features into a pre-trained intention classification model and outputting a user intention label and confidence; the emergency degree evaluation module is used for generating a dialogue emergency level based on the user intention label, the confidence coefficient and a preset emergency keyword library; the early warning execution module is used for triggering real-time early warning operation when the conversation emergency level reaches a preset threshold value; the real-time early warning operation comprises at least one of dynamically adjusting a robot dialogue strategy, generating a manual seat transfer instruction and upgrading a dialogue priority. The method can solve the problems that an existing voice outbound robot cannot accurately judge the user intention, and the conversation emergency degree recognition is insufficient, and improves the user experience and the overall efficiency.

The invention discloses a voice dialogue system based on a large model, and relates to the technical field of voice interaction, and the system comprises an intelligent scheduling module which determines a task type according to a to-be-recognized text, and dynamically adapts to a fast and slow thinking module according to the task type; the fast and slow thinking module dynamically adapts to the calculation unit according to the task type and outputs a feedback result; the voice interaction module generates a to-be-recognized text according to the voice characteristics of the user and generates a voice instruction based on a feedback result; the context management module stores the interaction log to a corresponding storage unit according to the index key value; the interaction log comprises a task type belonging to the same data flow, an adaptive path and a feedback result; and the data centralized control module determines a parameter adjustment strategy according to the performance index factors in the interaction logs, and the parameter adjustment strategy acts on the intelligent scheduling module or / and the fast and slow thinking module to optimize corresponding parameters. The intelligent balance of quick response and deep reasoning of the dialogue system under a single architecture is realized, and the real-time performance and accuracy of interaction are remarkably improved.

The present application relates to the technical field of speech recognition, and discloses a speech dialogue method and system, an electronic device, and a storage medium. The method of the present application comprises: in response to a speech audio stream of a first preset duration, generating a first streaming recognition result; obtaining a prediction result of a user speech request on the basis of the first streaming recognition result, obtaining a pre-request response result on the basis of the prediction result, and caching the pre-request response result; and in response to a speech audio stream of a second preset duration, acquiring the cached pre-request response result as a dialogue response result, the speech audio stream of the first preset duration corresponding to the incomplete user voice request, and the speech audio stream of the second preset duration corresponding to the complete user voice request. The speech dialogue method disclosed in the present application is a new and more efficient response acceleration scheme for a speech dialogue system, and can effectively improve the response speed of the speech dialogue system.

The invention provides a GAN-based digital doctor expression, action and emotion interaction simulation system. The system comprises a data set construction module, an audio encoder, an action mask encoder, a Transform converter, a training module and a digital doctor generation module. The data set construction module is used for constructing a high-quality medical scene data set; the audio encoder extracts advanced feature representation from the audio by adopting a pre-training model; the motion mask encoder is used for extracting motion feature information in a binary image with the same size as a video frame; the Transform converter is used for realizing the fusion of the multi-modal data; the training module is used for training the GAN network; and the digital doctor generation module generates a vivid whole body action and expression sequence through a trained generator. According to the system, expressions and actions of the digital doctor can be more accurately generated according to voice dialogues in the current system, and the problems that in a traditional online diagnosis and treatment system, users are not satisfactory, and the expressions of the digital doctor are not generated well are solved.

The invention relates to the technical field of voice interaction, in particular to a method and system for determining a voice reply strategy based on dynamic risk assessment, and the method comprises the steps: obtaining user input and calling a pre-trained large language model to output a risk score in response to a voice interaction request initiated by a user; grading the risk scores based on a preset risk threshold, wherein the risk scores comprise high risks, medium risks and low risks; if the risk is high, immediately entering a strategic refusal response process; if the risk is medium risk, entering a multi-round clarification dialogue process, and continuously recalculating a risk score based on the constructed clarification question and the answer of the user until the risk score is not in a medium risk interval; and if the risk is low, directly entering a normal interaction process. According to the invention, a strategy which can perform fine-grained evaluation and dynamic management and control on a multi-level risk scene and can adaptively switch rejection and clarification in the same closed-loop process can be constructed in a voice dialogue system, so as to give consideration to the interactive experience of safety compliance and natural smoothness.

The invention discloses a vehicle voice interaction method, apparatus and device, and a medium. The method comprises the steps of obtaining dialogue information of a driver and passengers in a target vehicle; inputting the dialogue information into a local large model deployed in the target vehicle, and analyzing and processing the dialogue information through the local large model to obtain standard question information; wherein the local large model is an offline large model, and the standard question information comprises at least one of optimization question information, a first prompt word and answer form information; sending the standard question information to a cloud big model for analysis and processing to obtain first reply information fed back by the cloud big model; and playing the first reply information based on the voice dialogue function of the target vehicle. According to the technical scheme, through cooperative processing of the local large model and the cloud large model, the accuracy, safety and user experience of vehicle voice interaction are effectively improved. The method can be widely applied to the technical field of vehicles.

The invention provides a voice dialogue interaction method and system for industrial equipment, and relates to the technical field of man-machine interaction, and the method comprises the following steps: obtaining a voice signal of a user, and carrying out the voice enhancement processing of the voice signal of the user through an incremental adaptive filtering algorithm, and obtaining an enhanced voice; according to the enhanced voice, using an information gain transfer learning method to identify an interaction intention of the user, and generating a to-be-interacted voice based on the interaction intention of the user; based on the enhanced voice, utilizing a time delay estimation method to identify an interaction position of the user, and performing position prediction on the position of the user; according to the position prediction result, an industrial equipment horn output strategy is constructed; and outputting the to-be-interacted voice based on the industrial equipment loudspeaker output strategy so as to realize voice dialogue interaction between the user and the industrial equipment. According to the invention, convenience, high efficiency and accuracy of interaction between the user and the equipment in an industrial scene are greatly improved, and intelligent development of industrial production is facilitated.

The invention relates to the technical field of medical emotion early warning, and discloses an early warning system used based on a hospital platform. The system comprises a data acquisition module which is used for acquiring a patient identifier and treatment time, and acquiring voice dialogue and text record content and associated information to generate a patient data set; the sentiment analysis module is used for analyzing semantic and acoustic features of the voice and text contents and generating a sentiment analysis result set; the grading processing module is used for carrying out hierarchical division on emotions and generating a patient emotion grading result set; the information synchronization module is used for synchronizing the grading labels and the patient identifiers to a hospital information system display terminal according to specifications and generating grading information synchronization records; the intervention execution module is used for matching an AI automatic pacifying or manual intervention strategy for the patients higher than the basic warning level, and generating an intervention execution record set; and the early warning triggering module is used for marking the patient with the emotion activation risk and generating an early warning triggering result. The system can sense emotion changes of a patient in real time, active intervention is achieved, and the diagnosis and treatment order is maintained.

The invention relates to the technical field of artificial intelligence and voice dialogue, and discloses a voice interaction method based on retrieval enhancement generation and multi-model collaboration and application thereof. Performing local multi-round intention recognition; performing local RAG retrieval and candidate aggregation; decision making and cloud generation; performing feedback, synthesis and persistence; the invention further provides application of the voice interaction method based on retrieval enhancement generation and multi-model collaboration. According to the method, through local structured intention recognition and RAG retrieval aggregation, in combination with the generation capability of a cloud large model, response timeliness and privacy protection are considered, and the recommendation accuracy and robustness in a multi-round voice interaction scene are remarkably improved; the retrieval redundancy is reduced and the context quality is improved through entity-level combination duplicate removal, rearrangement and fuzzy matching strategies; and the consistency of data updating and the stability of online service are ensured through an offline atom replacement mechanism, so that the terminal user experience is improved, and engineering deployment and expansion are facilitated.

The invention relates to an automatic depression risk assessment method based on a natural language processing technology. The method comprises the following steps: performing selective conversation content interviews with a subject by using a voice conversation function of artificial intelligence; dialogue recording and text data between the patient and artificial intelligence are obtained; performing automatic transcription and speaker separation on the original speech transcription text data, and constructing a structured question and answer dialogue sequence; generating a structured question prompt related to the depressive symptom by using a large language model, and splicing the structured question prompt with the original dialogue content; designing an artificial neural network pre-training language model coding word vector, fusing position coding, a self-attention mechanism, a problem-guided attention mechanism and a bidirectional long short-term memory network, and extracting deep semantic features related to depression risks; finally, continuous depression risk scores are output, correlation verification is carried out on the continuous depression risk scores and standard PHQ-8 scores, and the accuracy, robustness and interpretability of depression risk assessment are effectively improved.

The invention provides a voice dialogue task handover method and device, a server and a system, and the method comprises the steps: obtaining historical dialogue data of a voice dialogue task between a target user and first voice equipment; monitoring sensor data of a plurality of second voice devices of the first voice device in a preset neighborhood range; selecting a target voice device to which the first voice device is to be handed over from the plurality of second voice devices according to the sensor data; and handing over the voice dialogue task from the first voice device to the target voice device according to the historical dialogue data, so that the target voice device continues to perform voice interaction with a target user based on the historical dialogue data. By adopting the scheme of the embodiment, the technical problem that continuous voice interaction can only be carried out on a single voice device in the prior art is solved, and the fluency and intelligence of man-machine interaction are improved.

The invention discloses a robot control system and method based on AI voice, and belongs to the technical field of robot intelligent control. The system comprises a local voice processing module, a dialogue management and context understanding module, an instruction mapping and generating module and a robot communication and control module. The local voice processing module is integrated with a 16 kHz sampling ASR engine, voice-to-text conversion is realized through a 6-layer LSTM network and beam search decoding, and the TTS engine adopts a WaveNet architecture to synthesize voice. A 7 billion parameter large language model is arranged in the dialogue management module, a 32-layer Transform decoder architecture is adopted, 10 rounds of dialogue history is maintained, and intention recognition and entity extraction are achieved through a multi-head self-attention mechanism. And the instruction mapping module performs trajectory planning by adopting quintic polynomial interpolation and quaternion spherical linear interpolation. According to the invention, full-link localization processing is realized, the speech recognition delay is 180 milliseconds, the position error is less than 0.5 mm, and the problems of high delay, high privacy risk and weak complex instruction understanding ability in the prior art are effectively solved.

The invention discloses a streaming processing method and device for voice dialogues, electronic equipment and a storage medium, and relates to the technical field of audios and videos or other related technical fields, and the streaming processing method for the voice dialogues comprises the steps: receiving continuous voice streams, and obtaining historical dialogue texts corresponding to the voice streams; the voice stream and the historical dialogue text are input into a streaming processing model, a streaming voice fusion feature vector is output, and the streaming processing model carries out feature extraction on the voice stream based on a state space model and a dynamic selection mechanism; inputting the streaming voice fusion feature vector into a language processing model, and outputting a response text; and generating a response audio based on the response text, and returning the response audio to the user side. According to the invention, the technical problem of low voice conversation processing efficiency under a cascade architecture in the prior art is solved.

Dialog in a language unfamiliar to an editor poses obvious challenges during the media editing process. It is nearly impossible to edit media containing spoken dialog without a clear comprehension of the underlying language. The methods described here use a combination of artificial intelligence and machine learning models to generate a language proxy in which the dialog is translated into a language that is familiar to the media editor. The editor is then able to edit the media composition in their own language. To generate an edited media composition with spoken dialog in the original language, the edited language proxy is synchronized with and linked back to the original media. The methods combine automatic speech recognition, translation, speech to text, and voice cloning together with existing non-AI technologies such as captioning and media relinking.

The invention provides a personality prediction method and device based on voice conversation, electronic equipment and a medium. The method comprises the following steps: acquiring conversation voice information between a to-be-predicted user and an intelligent agent; extracting a target dialogue feature and a dialogue log of the to-be-predicted user from the dialogue voice information; according to the dialogue log and the target dialogue feature, updating the dialogue log and dialogue summary information of the to-be-predicted user; based on the fused target dialogue features, the updated dialogue log and the dialogue summary information, obtaining at least one prediction label of the to-be-predicted user; and inputting the user standardized text description information obtained based on the at least one prediction label fusion into a pre-trained large language model, so that the large language model outputs a personality prediction result of the user to be predicted. Therefore, the accuracy of personality prediction of the to-be-predicted user can be improved.

The invention relates to the technical field of artificial intelligence, and particularly provides a tax hotline consultation agent method and device, and the method comprises the following steps: S1, directly obtaining a session audio stream from a telephone end through a hardware telephone line universal demultiplexer RJ9, and carrying out the analysis; s2, converting the voice dialogue between the seat personnel and the taxpayer into a text form in real time, and performing voice transcription in real time; s3, performing deep analysis on the text content generated by real-time voice transcription; s4, constructing a tax knowledge graph; s5, accurate and detailed answers are automatically generated for the tax consultation questions of the clients; s6, extracting key information from the dialogue content, and performing structured processing for subsequent summarization and extraction; and S7, feeding back the generated dialogue summary and question answers to the seat personnel, and evaluating and modifying the summary content and the question answers by the seat personnel. Compared with the prior art, accurate and comprehensive information support can be provided for seat personnel, and the customer service quality and the working efficiency are improved.

The invention relates to a method and equipment for generating BI based on voice conversation and a storage medium, and the method comprises the steps: collecting and preprocessing voice, then carrying out voice recognition and transcription, and carrying out the intention understanding and semantic analysis of a transcribed text in combination with a natural language processing technology; automatically generating a corresponding data query statement or code according to a semantic analysis result; generating a visualization scheme according to the visualization requirements obtained by semantic analysis and the characteristics of the data analysis result; establishing connection with a plurality of data sources, integrating and preprocessing data acquired from different data sources, and setting data cache and management; and according to the generated visualization scheme, generating a visualization chart by using a visualization library, realizing an interaction function of the visualization chart, and realizing multi-device adaptation of visualization display. According to the method, a user can interact with the system through a natural language without learning complex query grammar and operation process, so that the convenience of data analysis and the user experience are greatly improved.

The invention discloses a voice model testing method and device, equipment, a storage medium and a program product, and relates to the technical field of model testing, and the method comprises the steps: obtaining a current operation state of a voice model; in response to the current operation state being a test state, a voice test data set is acquired, the voice test data set is acquired and generated in advance through a client where the voice model is located, and the voice test data set at least comprises a plurality of dialogue audios; performing a voice dialogue test on the voice model according to the dialogue audio in the voice test data set to obtain a reply audio generated by the voice model for the dialogue audio; and generating a test result of the voice model based on the matching degree of the dialogue audio and the reply audio. According to the invention, the reproducibility and stability of the test data are improved, the quantitative evaluation of the test result is realized, and the test reliability of the voice model is improved.

The invention relates to the technical field of model voice interaction, and particularly discloses a multi-agent collaborative medical stroke follow-up visit voice dialogue system and a construction method thereof. According to the method, the voice interaction model, the planingagent module, the knowledge retrieval agent module, the quistirewriting agent module and the messagagent module are set as system components, the knowledge retrieval agent module establishes a database by crawling real and reliable stroke professional knowledge, the illusion of compiling of a large model can be avoided, the quistirewriting agent module and the planingagent module are matched to act, the knowledge retrieval agent module, the quistirewriting agent module and the messagagent module are matched, and therefore the interestingness of the system is improved, and the interestingness of the system is improved. According to the method, the long problem generated in the interaction process can be analyzed into a plurality of sub-problems, errors in the problem are corrected, deviation of the system in interaction information analysis is avoided, and the analysis capability and stability of the system are effectively improved.

A contact center server provides as part of a voice conversation with a customer device a voice prompt indicating the unavailability of any voice agent the agent devices and an option to route the voice conversation to any available chat agent at one of the agent devices. The contact center server receives a confirmation from the customer device to route the voice conversation to any available chat agent. In response to the confirmation, a multimodal communication session between the customer device and an available chat agent is established. Subsequently, the contact center server orchestrates a multimodal conversation in the multimodal communication session by speech-to-text conversion of customer messages received from the customer device, and text-to-speech conversion of agent messages received from the available chat agent with whom the multimodal communication session is established.

An interactive care robot according to an embodiment of the present disclosure includes: at least one sensor including a microphone configured to receive voice conversations with a user; a memory configured to store instructions; and a processor operatively connected to the memory and configured to execute the instructions. The processor is configured to: generate conversation history information based on the conversations with the user; generate user information and classify the user information into predetermined categories; set a priority of a care service to be provided to the user based on the classified user information and the conversation history information; and select a care service to be provided to the user based on the set priority and control components of the interactive care robot to perform the selected care service.

The invention provides an exhaustion report generation method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring object transaction data of a plurality of candidate objects; performing object identification on the object transaction data based on a preset identification strategy, and screening out at least one target object from the plurality of candidate objects; determining a target exhaustion verbal skill template matched with each target object in the at least one target object; for each target object, initiating a call outbound to the target object based on the target exhaustion call skill template to obtain an exhaustion voice dialogue of the target object; and generating a target exhaustion report of the target object based on the exhaustion voice dialogue. According to the method, full-link automatic customer full-duty investigation can be realized.

The utility model discloses a guest room control system with service reminding and sleep aiding sound effects, and relates to the field of intelligent services. The guest room control system with the service reminding and sleep-aiding sound effects comprises a reminding service module which is arranged on the wall of a guest room and is used for carrying out voice reminding and sending different reminding music at the set time of a user after the customer sets the reminding type and the reminding time; the music playing module is arranged on the wall of the guest room and is used for providing various types of sleep-aiding music for the guest room; the voice conversation module is arranged beside a bedside table of a guest room and is used for voice communication between a worker and a customer; and the control module is arranged at the reception desk of the hotel, and the control module is in communication connection with the reminding service module, the music playing module and the voice conversation module. According to the system, a manager can provide various intelligent services, such as reminding, music and voice communication services, in a guest room for a customer, the individual requirements of the customer are met, and the check-in experience feeling of the customer is improved.

The embodiment of the invention provides a voice dialogue job management method based on a large model, a program product, equipment and a medium, and relates to the technical field of artificial intelligence. In the outbound operation process of a user, the outbound record information of this time is input into a pre-established large model to obtain first outbound operation management information used for indicating next outbound operation or second outbound operation management information used for indicating ending of the outbound operation, and if the first outbound operation management information is obtained, the outbound record information of this time is input into the large model, and the outbound record information of this time is input into the large model. If the first outbound operation management information is obtained, next outbound operation is carried out on the user according to next outbound task information in the first outbound operation management information, and if the second outbound operation management information is obtained, the outbound operation on the user is ended. The large model is utilized to flexibly judge whether to carry out next call-out on the user or not and determine execution details of the next call-out task according to the call-out condition, so that the call-out operation process of the user is flexibly managed, and maximization of service benefits is facilitated.

The invention provides an artificial intelligence AI voice dialogue consultation control system which comprises a base, a machine cabinet is fixed to the upper end face of the base, a consultation host is installed at the top of the machine cabinet, a cleaning structure is arranged in the machine cabinet, a receipt printer and a card reader are installed on the side wall of the front side of the machine cabinet, and the card reader is arranged on the side wall of the front side of the machine cabinet. A code scanner is installed on a transverse table of the machine cabinet, an installation frame is fixedly installed in the machine cabinet, a loudspeaker and a microphone are installed on the installation frame, and a camera is fixed to the front side wall of the top end of the machine cabinet. Through the cleaning structure, the spray pipe, the atomization nozzle, the branch pipe, the liquid supply structure and the push-out air drying structure, the voice conversation consultation terminal can be automatically disinfected and wiped, and dust on the surface of the voice conversation consultation terminal can be cleaned; the problems that in the prior art, cross infection is prone to occurring when multiple persons use the display screen, and the customer experience is affected by dust accumulated on the display screen are solved.

The present disclosure provides a voice dialogue execution method, an electronic device and a storage medium, and relates to the technical field of voice interaction. The specific implementation scheme is: in response to a voice request of a user, generating semantic request information corresponding to the voice request, the semantic request information comprising intention information; determining a target execution domain according to the semantic request information; and generating a dialogue result of the current round of dialogue based on the target execution domain. By using the technical scheme of the present disclosure, the semantic request information containing the intention information can be generated according to the voice request of the user, the target execution domain for executing the current round of dialogue can be determined in the dialogue engine, the dialogue result can be quickly obtained, the efficiency of the dialogue engine in processing the voice request of the user and the flexibility of voice jumping are improved, the threshold for the user to use the multi-round voice dialogue is reduced, and the interactive function is enriched.

This contributes to the realization of a dialogue system that makes it easier for users to obtain the answers they expect. [Solution] The learning system (1) comprises an acquisition means (11) for acquiring driver information relating to the actions of the vehicle driver, a generation means (12) for generating learning data based on the driver information, and a learning means (13) for fine-tuning a base model relating to a dialogue system that performs voice-based dialogue with the driver using the learning data.