314results about "Audio data indexing" patented technology

The invention discloses a digital intelligent teaching recording and broadcasting system and method, and relates to the technical field of data encryption, and the method comprises the steps: collecting teaching videos and audios of a teacher through a high-definition camera and an audio device, carrying out the preprocessing, obtaining the course content, recognizing the key information of the course content through a natural language processing NLP and computer vision technology, and carrying out the recording and broadcasting. The method comprises the following steps: segmenting a video into single knowledge point fragments, performing classified storage, forming a learning resource library, collecting basic information and learning habit data of students, constructing a user portrait, matching learning resources, extracting the learning habit data in the user portrait, performing feature extraction, and obtaining a comprehensive feature vector; constructing a learning state evaluation model by using a convolutional neural network to comprehensively analyze the comprehensive feature vector to obtain a learning state comprehensive score, formulating a playing strategy according to the learning state comprehensive score and matched learning resources, regularly testing knowledge points of students, evaluating the mastering degree of the students, and updating a user portrait according to a result.

The invention provides an acoustic data storage and retrieval method combined with computer cloud computing, which comprises the following steps of: performing time sequence division processing on original acoustic data to generate an audio frame sequence with a timestamp mark; based on a context window of the audio frame sequence, acoustic features are extracted, and a context-aware acoustic feature vector is constructed; constructing a time sequence sensing distributed index structure according to the acoustic feature vector, and dynamically storing the streaming acoustic data to obtain the time sequence sensing distributed index structure; and executing cross-modal similarity retrieval on the query audio and the distributed index structure to obtain a target fragment sequence in space-time association with the query audio. By adopting the method, the retrieval precision and efficiency of the acoustic data in a complex time sequence association scene can be improved through a time sequence perception storage architecture and a cross-modal retrieval mechanism.

The invention discloses an intelligent interaction system for recognizing voiceprint information through environmental sound, and relates to the field of man-machine interaction. Comprising an environment sound pickup module which picks up environment sound in a vehicle by using a microphone array and carries out filtering and denoising processing on the sound; the voiceprint feature extraction module is used for converting the sound signal into a spectrogram by using short-time Fourier transform, distinguishing different passengers through different waveform features, and then extracting MDCC features in the sound signal as sound feature vectors; according to the invention, through picking up the environment sound, then extracting the voice data of the passenger, carrying out feature extraction on the voice data again, obtaining the voice content of the passenger, carrying out emotion and intention analysis on the voice content of the passenger, and then carrying out recommendation and related control, the active degree and the automation degree of man-machine interaction are increased, and the experience of the passenger is improved.

A method and system for providing playback of air traffic control (ATC) communications for a pilot of an aircraft has been developed. First, an audio communication is received from the ATC for the pilot of the aircraft. The audio communication is segmented into three separate audio channels including: a raw channel of the audio communication as received, an enhanced channel of a filtered version of the audio communication, and a synthesized channel of a speech synthesized version of the audio communication. An identification function identifies segments of each audio communication with reference to identifying data for the aircraft. The separate audio channels are then stored in an electronic memory for later retrieval by the pilot of the aircraft.

A system and method for media content management include creating, via a digital vault, a container file comprising media content submitted by a first user and content metadata; verifying, via the digital vault, a completeness of the content metadata associated with the media content in the container file; classifying, via the digital vault, the container file based on the completeness of the media content; capturing, via the digital vault, event metadata when a second user gains access to the container file, the event metadata comprising at least one of identification of the second user, an activation timestamp, a duration of access, portions of the container file accessed, and changes to the container file; and enabling a private communication channel between parties affiliated with the media content to permit messaging among the parties affiliated with the media content via the private communication channel.

A voice registration device includes an acquisition unit configured to acquire a voice signal of an utterance voice of a speaker, an emotion identification unit configured to identify at least one type of emotion of the speaker included in the voice signal, and a registration unit configured to register a voice signal for the each type of emotion in a database based on an identification result by the emotion identification unit.

The invention relates to the technical field of computers, in particular to a historical audio record display method, electronic equipment and a computer readable medium. The method comprises the steps that it is detected that a first triggering condition is met at the first moment, first information is displayed, and the first triggering condition is set by a user before the first moment through second electronic equipment; when it is detected that a second trigger condition is met at a second moment, second information is displayed, the first information and the second information are determined based on first audio data and second audio data collected by second electronic equipment in a recording mode, and the second trigger condition is set by the user before the second moment through the second electronic equipment. The method supports recording of related voices of daily life items or work items and the like participated by a user in a recording mode in a historical time period, displays corresponding recorded or generated first information to a specific person in a specific scene and specific time, and provides functional services of recording, memorizing, tracing and the like for the user.

The invention provides an enterprise call-out method, device and equipment and a storage medium, and the method comprises the steps: obtaining the enterprise information of a to-be-called customer, converting the enterprise information into a label, and carrying out the matching of verbal skill contents from a historical verbal skill database according to the label, and obtaining a personalized verbal skill list; real-time voice recognition is carried out on an exhaustion call record collected on an exhaustion call site to obtain a real-time text, keyword retrieval is carried out on the real-time text, the real-time text is compared with the personalized verbal skill list, violation items and omission items are obtained respectively, and the violation items and the omission items are used for generating reminding information and sending the reminding information to exhaustion call personnel; after the exhaustion call process is finished, performing voice recognition on the exhaustion call record to obtain a full text, extracting key information from the full text and filling the key information into the report template to obtain an exhaustion call report; and acquiring the position information of the call-out site and the voiceprint characteristics of the call-out record, verifying the position information and the voiceprint characteristics, and marking the call-out report according to the verification result. The problem that in the prior art, the complete dispatch authenticity verification capability is weak is solved.

The invention discloses a training method and system and an application method and system of a voice conversion model based on data distillation. The method comprises the following steps: establishing a voice training data set, and training an original voice conversion model by using the voice training data set to obtain an initial voice conversion model; establishing a voice evaluation data set, and inputting the voice evaluation data set into the initial voice conversion model to obtain conversion voice data of each corresponding speaker; calculating a voice conversion score of each speaker; judging whether the voice conversion score of each speaker reaches a preset condition or not; if not, removing the voice data corresponding to the speaker from the voice training data set, and taking the remaining voice data as a voice database; repeatedly training; and taking the initial voice conversion model and the voice database as a trained voice conversion model and a final voice database respectively. The voice conversion model and the voice database obtained through training of the method can support conversion of various timbres, and the voice conversion effect is good.

The invention discloses an activity information retrieval method and device based on a large model and a medium, and the method comprises the following steps: obtaining enterprise business system data, and carrying out associated field integration processing on the enterprise business system data to obtain a business field wide table; converting preset activity audio data into activity text data, and storing the activity text data to an audio data storage position in the business field wide table to obtain a to-be-processed business field wide table; based on the to-be-processed business field wide table, a business field wide table for retrieval is obtained through mapping table description analysis of field description; obtaining audio resource data through supplementary retrieval processing according to the business field wide table for retrieval; and obtaining a user query text, and determining required information data through SQL conversion based on the user query text and the audio resource data. By means of the method, the technical problems that in the prior art, activity data retrieval is low in efficiency and inaccurate are solved.

A music recommendation system according to one embodiment of the present invention includes: a text receiving unit for receiving diary text input to a user terminal; an emotion extraction unit for extracting a diary emotion vector for the diary text using an artificial intelligence model on the basis of the diary text; and a music recommendation unit for determining a piece of recommended music information corresponding to the diary text among pieces of music information in a database on the basis of the diary emotion vector.

The invention discloses a hierarchical rhythm mapping-driven short video copywriting mood automatic adjustment method, and relates to the technical field of video processing, and the method comprises the steps: 1, receiving a text character string and a language type identifier, and building an occupation column for bearing a tone mark, an accent mark and a duration mark at each level; 2, dividing each sentence into phrase segments based on the hierarchical index table, freezing boundaries by taking the phrase segments as units, presetting sentence end termination styles according to punctuations, determining kernel phrases according to semantic anchor points, initializing trends of the kernel phrases, and performing time sequence elastic alignment and hierarchical backfilling to obtain a sentence end termination pattern; and finally outputting a triple sequence which covers all syllables and is composed of tone marks, accent marks and duration marks as a target rhythm control sequence. And step 3, performing audio generation based on the target rhythm control sequence to obtain new dubbing. According to the method, the tone accuracy and expressive force of short video dubbing are improved, and the time and cost of manual adjustment are remarkably reduced.

The invention relates to a space monitoring system and a space monitoring method using sound signals. The present invention proposes a technique for organizing the frequency response of a space and related data to construct a database so as to easily, quickly, and accurately determine the situation of a space to be monitored, and a technique for performing space monitoring using the same.

The invention relates to the field of voice signal processing, in particular to a multi-language interactive learning system based on voice recognition, which is characterized in that sound waves and mouth shape images are synchronously acquired and discretized by the system, and cross-modal coding is formed after alignment; secondly, the code is injected into a micro-ring photon reserve network through phase modulation to unfold time sequence characteristics, the code is mapped into a quaternion graph to be embedded, and segment boundaries are extracted through a diffusion-pulse coupling method; then, according to a fixed field sequence, encapsulating the quaternion graph embedding and segmentation data into an object mark prompt, inputting the object mark prompt into a low-rank adaptive language model, and generating semantic segmentation data and text transcription; and finally, the adaptive learning module implements sparse gradient updating on the low-rank weight and pulse network by using an integer fractal hash exclusive-or difference mask, and adopts support-query element learning for synchronous iteration after user clarification. According to the system, low-power-consumption, high-precision and second-level accent self-adaptive multi-language voice interaction is realized on the end side.

A system configured to perform content identification using fingerprinting to recognize known media content. The system may generate a reference database including reference fingerprints for each media content item to include in the content identification. In addition, the system may generate a hash table that associates individual frames of the reference fingerprints with identification information for corresponding media content items. When a device is playing media content, the system may perform content identification by generating query fingerprints representing the media content and comparing the query fingerprints to the reference database. For example, the system may match a query fingerprint to a reference fingerprint by identifying which of the reference fingerprints shares the most frames with the query fingerprint using the hash table. In addition, the system may use additional decision criteria to confirm a match, such as fine-grain matching or tracking successive fingerprints over time.

A computing system is configured to obtain a plurality of media files that each includes speech of one or more speakers. The computing system is further configured to process the plurality of media files to generate indexed data, wherein the indexed data includes a corresponding embedding for each speaker of the one or more speakers identified in the media file and a corresponding one or more keywords identified in the speech in the media file. The computing system is further configured to receive an indication at least one of a selection of a particular speaker from the one or more speakers or a selection of a particular keyword from a plurality of keywords. The computing system is further configured to generate one or more correlations based on the indexed data. The computing system is further configured to output an alert regarding the one or more correlations.

According to an embodiment, a trained AI is provided that automatically identifies stems of a music work and loops within the stems. Information about the stems, the cut points of loops, and the loop's fundamental parameters will be formed into an AI Song pack. The remixing step uses the AI Song pack as a starting point and a database of loops is searched to identify audio loops that can replace loops with similar sonic characteristics in the music work to create a remix. Once some number of candidate loops have been identified a final remixed audio track will be produced which is comprised of replaced loops from the database. Alternatively, replacement stems might be created by replacing all loops in each stem. Finally, effects might be applied to the audio material created by either approach.

Implementations described herein relate to methods, systems, and computer-readable media to automatically answer a call. In some implementations, a method includes receiving a call from a caller device at a client device. The method further includes determining, based on an identifier associated with the call, whether the call matches auto answer criteria, and yin response to determining that the call matches the auto answer criteria, answering the call without user input and without alerting a user of the client device. The method further includes generating a call embedding for the call based on received audio of the call, comparing the call embedding with spam embeddings to determine whether the call is a spam call, and in response to determining that the call is a spam call, terminating the call.

The invention relates to an audio production model file creation method and electronic equipment. The method comprises the steps of obtaining an original audio file; analyzing the original audio file through a renderer, and generating corresponding preset metadata elements; wherein the preset metadata elements comprise an audio program element, an audio content element, an audio object element, an audio track unique identification element, an audio packet format element, an audio channel format element, an audio stream format element and an audio track format element; based on the relation between the preset metadata elements, establishing a reference relation of the corresponding elements; generating a metadata file from the preset metadata elements according to the preset metadata elements and the reference relationship; creating a channel allocation file for connecting the metadata file and an audio track of the original audio file; and establishing a guide relationship between the metadata file and the channel allocation file, and generating an audio production model file.

An electronic device according to an embodiment comprises a memory, a display, and a processor operatively connected to the memory and the display, wherein the processor may be configured to: collect speech data; match the collected speech data with user information related to the collected speech data and store, in the memory, association information between the collected speech data and the user information; when generating content, detect speech data of the content input that is input during generation of the content; and when there is user information matching with the detected speech data in the memory, store the user information matching with the detected speech data of the content as tag information of the content.

The invention provides a music data processing method and device, electronic equipment, a non-instantaneous computer readable storage medium and a computer program product, and belongs to the technical field of music data processing. The method comprises the following steps: acquiring music data; marking the music data as a predetermined music structure according to a first preset rule; wherein the preset music structure comprises at least one of music segments, music sentences, music knots and phonetic types; marking the preset music structures as preset attributes according to a second preset rule, and marking the relationship between the preset music structures to form marked music data; according to the method, the annotated music data is stored in the corresponding data table of the database, the problem that annotation of the music data cannot meet training data requirements in the prior art is solved, and the quality and efficiency of annotation of the music data are improved, so that the training data requirements are better met, and data support with annotations is provided for subsequent task research.

Described herein is a computer implemented method. The method includes displaying, on a display, a scene timeline including a time-ordered sequence of scene previews, each scene preview corresponding to a scene of a video production and having a display width that provides a visual indication of a duration of that scene. The method further includes displaying a canvas including a first visual element that is associated with the first scene, and in response to detecting selection of the first visual element from the canvas, causing a first visual element timing indicator to be displayed. The first visual element timing indicator is aligned with the scene timeline based on a first visual element start time and a first visual element end time.

The invention relates to the technical field of audio processing, in particular to an audio gain output dynamic adjustment method and device, equipment, a storage medium and a computer program product. The method comprises the following steps: establishing a corresponding volume sequence based on initial audio data, and storing the volume sequence in a local database; based on the volume operation instruction of the user, updating the gain parameter, and recording boundary information corresponding to the volume operation instruction in a local database; determining a target playing range according to the boundary information, and generating a mapping relation between the input volume and the output volume; based on the mapping relation, processing the initial audio data by adopting a preset edge calculation algorithm to obtain an adjusted audio frame; and controlling the audio and video playing device to output the adjusted audio frame according to the updated gain parameter, thereby improving the audio playing quality of the audio and video playing device.

The invention discloses a voice dialogue retrieval method and device based on a large model and a medium, and belongs to the technical field of voice retrieval. The method comprises the following steps of: constructing a to-be-retrieved and inverted index database, storing character fields in the previous database, and converting pinyin in the later database; and guiding the user to input the retrieval voice by using the preset verbal skill template. The method comprises the following steps: converting voice into pinyin retrieval information through a voice recognition large model, comparing inverted indexes by using a fuzzy matching algorithm, and screening high-matching-degree fields; if the number of the matched fields is large, screening voice is generated for further inquiry; if not, prompting the user to re-input or correct the input; and when the matching degree is 1, directly determining a retrieval field. Finding a result in a to-be-retrieved library according to the field, and uniquely and directly replying; if not, the missing field is recognized and inquired for accurate retrieval. And whole-course verbal skill template guiding. By means of the method, the effects that the retrieval mode is flexible, and the cold start cost is low are achieved to a certain extent.

A system and method for processing and actionizing structured and unstructured experience data is disclosed herein. In some embodiments, a system may include a natural language processing (NLP) engine configured to transform a data set into a plurality of concepts within a plurality of distinct contexts, and a data mining engine configured to process the relationships of the concepts and to identify associations and correlations in the data set. In some embodiments, the method may include the steps of receiving a data set, scanning the data set with an NLP engine to identify a plurality of concepts within a plurality of distinct contexts, and identifying patterns in the relationships between the plurality of concepts.

The invention provides a design method based on a Chinese characteristic digital triple tone test library, which comprises the following steps: determining a more easily confused digital group through a similarity estimation formula and a perception distance formula, determining an audiometric material according to a preset condition, and correcting according to a correction factor formula to obtain a corrected audiometric material. The method comprises the following steps: randomly performing three-three combination to form a plurality of initial triple tones, performing scoring according to a preset scoring rule according to a preset speech frequency range to form a triple tone library conforming to frequency coverage, obtaining a to-be-optimized triple tone library according to a digital initial rhyme statistical table, determining a sum score of each triple tone in the to-be-optimized triple tone library according to an attribute table, and sorting and screening the to-be-optimized triple sound library according to the sum score to form an optimized triple sound library, traversing the optimized triple sound library, and screening out a final digital triple sound test library according to a preset balanced digital frequency in combination with the triple sound sum score. The use method comprises the following steps: disrupting the test library, adjusting stimulation sound intensity according to patient answers, calculating a signal-to-noise ratio, and obtaining a final hearing evaluation index.

Example implementations include dividing a textual transcript of digital audio content into a sequence of chunks, where the chunks are chronologically non-overlapping; determining annotations for each of the chunks, the annotations including at least one of: a title of the digital audio content, a description of the digital audio content, or one or more inferred segment titles of one or more previous segments of the digital audio content; providing, to a natural language model, a first chunk from the sequence of chunks, an associated annotation, and instructions to identify: a segment found in the first chunk, and a segment title of the segment; receiving, from the natural language model, an indication of the segment and the segment title; and storing the indication of the segment and the segment title as metadata associated with the digital audio content.

A data structure embodied on a computer-readable medium is disclosed. The data structure may include database schema such as a structured query language (SQL) database. The database schema may include a registration schema that cooperates with a competition schema to award contestants engaged in a game of skill. The competition schema may encourage contestants to participate in games of skill related to songs, artists, and / or albums.

Method (140, 200) and apparatus (120, 270) for characterizing digital content (124) using an artificial neural network (ANN) engine (122, 274). Computer data sets (126, 128, 130, 132, 134, 160, 202, 232, 242, 302, 332) from a library store (124) are processed to generate a corresponding sequence of multi-dimensional embedding vectors (162, 172, 182) in a latent space (170, 180). The embedding vectors are grouped into intervals or segments (166A, 168A, 228A) of the data sets based on movement metrics (164, 166, 168, 228) associated with the embedding vectors. A representative vector, RV (174A, 184B, 210, 276) is selected for each group. Thereafter, in response to a query input (272), selected intervals among the various computer data sets are identified and output based on a similarity measure (278) between the RVs and a search vector derived from the query input (150). Further embodiments provide a transformation model (322, 334) that transforms the embedding vectors and / or the RVs from a first latent space based on a first embedding model (304, 314, 332) to a different, second latent space based on a second embedding model (316, 338).

Audio data comprising speech is received at a first client device executing an application in an artificial reality environment, in which the first client device is associated with a speaking user. A determination is then made as to whether an object associated with the speaking user is within a field of view of a listening user of a second client device executing the application. The audio data is modified based at least in part on a set of rules and whether the object associated with the speaking user is within the field of view of the listening user. The modified data is then communicated to the listening user of the second client device.