185 results about "Punctuation" patented technology

The invention relates to the technical field of data processing, in particular to a method and system for processing data based on a large language model.The method comprises the following steps that based on inter-sentence punctuation positioning and part-of-speech tagging, sentence blocks are divided to generate functional partitions, themes and relational words are extracted to judge semantic chain starting points, a trigger index sequence is constructed, and logic jump points and breakpoint positions are recognized; and mapping the label structure to the language model output analysis deviation, and generating a label mapping combination list. According to the method, semantic turning nodes can be captured by analyzing the semantic direction change trend, the relation between the semantic turning nodes and verb and noun combinations is judged, the position of a trigger point of an actual information transfer effect is extracted, and the break point area of a semantic path is recognized through the positioning of key word starting and stopping blocks and the logical judgment of noun group cross combination; the path integrity has a clear fracture identifier, a traceable semantic mapping structure path is established in a language model, and the accuracy, coherence and hierarchy clearness of semantic reconstruction are enhanced.

The invention discloses a Chinese named entity recognition system, method and equipment based on multi-scale features and a medium, and the method comprises the steps: decomposing an original text into a character sequence through a preprocessing module, and preprocessing characters, including removing punctuation marks and uniformly converting the characters into lower letters; a RoBERTa-WWM sub-module of a feature extraction module is responsible for converting an input text into a high-dimensional feature vector, a CNN sub-module effectively extracts local features through a sliding window mechanism, and a BiLSTM sub-module finally utilizes the advantage of bidirectional processing to obtain complete context information; decoding the hidden state representation by using a dynamic conditional random field (CRF) through a sequence tagging module to determine an optimal tag sequence; according to the method, pre-training, multi-scale feature fusion and dynamic decoding technologies are integrated, and efficient and accurate Chinese entity recognition is realized; through a unique preprocessing rule, a modular architecture design and optimized hyper-parameter configuration, the performance and robustness of the system in a complex scene are ensured.

The invention relates to the technical field of aggregation retrieval, in particular to a distributed aggregation retrieval method for a law and regulation text database, which comprises the following steps: collecting and integrating law and regulation text data, preprocessing the law and regulation text data, removing useless punctuations and blank characters, and generating a preprocessed text set. According to the method, data integration and preprocessing are carried out on the regulation text, useless punctuations and redundant blank characters are effectively removed, the purity of text data is guaranteed, and the accuracy of subsequent word segmentation and word frequency statistics is improved; the implementation of the word segmentation and word frequency statistical process is helpful for identifying key feature vocabularies in the regulatory text, so that the accuracy of the subsequent inverted index construction stage is enhanced; by preliminarily constructing the inverted index and implementing similar item merging and low-frequency vocabulary removing operation, the index scale and redundant interference are reduced, and the index query efficiency and accuracy are improved.

Embodiments of the present disclosure relate to a method and apparatus for speech translation, an electronic device, and a medium. The method includes obtaining an audio in a source language, where the audio includes a specific type of information. The method further includes obtaining prompt content related to a target language. In addition, the method further includes generating, based on the audio and the prompt content, a target-language text corresponding to the audio, where the target-language text includes a punctuation mark corresponding to the specific type of the information.

The invention discloses a text error correction method and device based on GRU-Transform, electronic equipment and a storage medium, and belongs to the technical field of text processing. The method comprises the following steps: acquiring a plurality of data sets, wherein the data sets comprise a spelling error data set, a grammar error data set, a punctuation error data set and a similar word error data set; constructing a text error correction data set based on the plurality of data sets; a text error correction model is trained based on the text error correction data set, the text error correction model comprises a feature extraction sub-model, a feature fusion sub-model, a coding-decoding sub-model and a loss calculation sub-model, and the coding-decoding sub-model is a GRU-Transform model; and inputting the to-be-corrected text data into the trained text error correction model to obtain an error-corrected text output result, thereby improving the accuracy and applicability of text error correction.

The invention discloses a false comment perception method based on semantic and emotion joint modeling, and belongs to the technical field of natural language processing. The method aims at solving the problem that in the prior art, Chinese false comments cannot be effectively processed. The method mainly comprises the following steps: firstly, segmenting a comment text to be detected into ordered clause sequences based on turning links and punctuations; secondly, extracting features in parallel by adopting a double-flow architecture: generating a global semantic representation vector by one semantic flow through mask language modeling (MLM) and a hierarchical attention mechanism; the other emotion flow generates an emotion vector for each clause, an emotion covering modeling (MSM) auxiliary task is innovatively introduced to learn logic coherence of emotions, and finally a global emotion dynamic vector is generated; then, fusing the two vectors; and finally, judging the authenticity of the comments through a classifier. According to the method, semantic and emotional dynamics are deeply fused, a multi-layer attention mechanism is introduced, Chinese false comments can be recognized and perceived more accurately, and the method has high application value.

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.

1. Name of the Design Product: Graphical User Interface for Displaying Dial Information of an Electronic Device. 2. Use of the Design Product: For an electronic device. 3. Design Key Points of the Design Product: Lies in the interface of the graphical user interface. 4. Picture or Photograph that Best Illustrates the Design Key Points: The front view of Design 1. 5. Design 1 is designated as the basic design. 6. Use of the Graphical User Interface: Graphical user interface for displaying dial information. 7. Human - Machine Interaction Method of the Graphical User Interface: The front views of Design 1 to Design 4 are interfaces for displaying dial information. 8. Other Situations Requiring Explanation: Other views are omitted. The "X" in each view represents replaceable or variable text, numbers, or punctuation marks.

A method includes obtaining initial transcription for input natural speech; performing segmentation of initial transcription into text portions, based on punctuation marks in initial transcription; determining segment-level timestamps for text portions based on the input natural speech; performing audio segmentation on input natural speech, by cutting input natural speech based on segment-level timestamps, to obtain audio chunks; generating transcription portions for each of the audio chunks; merging transcription portions to form re-transcription; determining word-level timestamps for re-transcription, by aligning input natural speech against re-transcription; calculating silence time periods, each corresponding to silence between each two adjacent words of input natural speech, based on word-level timestamps; performing a final segmentation on input natural speech and re-transcription, based on silence time periods, to generate final audio segments and corresponding final transcription portions. The final audio segments and corresponding final transcription portions may be included in training dataset for training a model.

A speech condensation processing system and method includes an ASR system for a source language that receives an audio stream with speech and outputs at least one word sequence and time stamps in the language spoken, a memory that stores a condensation program and corresponding data and databases that store training data, which may include manually condensed data, two-way translated data, and aligned subtitle data, and a processor coupled to the ASR system and memory that executes the condensation program to format and condense text by transforming the at least one word sequence from ASR into human-readable text with proper casing and punctuation, and condenses the text based neural training to remove words from the at least one word sequence that are not relevant for meaning.

The invention relates to the field of teaching interaction quality evaluation, in particular to a teaching interaction quality evaluation method and system based on a large language model. The method comprises the following steps: audio transcription: converting classroom audio into an original transcription text through voice activity detection, speaker classification, automatic voice recognition and punctuation recovery; transcriptional refining: performing context-based text error correction on the original transcriptional text by using a large language model in combination with a preschool education field knowledge base to generate a refined transcriptional text; a quality evaluation step: based on a preschool education quality evaluation scale, using few sample example guidance and thinking chain reasoning for each scoring point, judging whether a voice segment conforming to the scoring point exists in the refined transcriptional text, performing binary scoring, and determining whether the voice segment conforms to the scoring point; and generating an interactive quality evaluation report containing the standard-reaching rate of each evaluation dimension, teaching bright spot analysis and staged teaching optimization suggestions. The evaluation efficiency is remarkably improved. The method is suitable for teaching interaction quality evaluation.

The invention discloses a large model training method and device, a voice recognition text processing method and device, equipment and a medium, relates to the technical field of communication, and aims to improve the accuracy of text output obtained by a post-processing task. The method comprises the steps that text data sets used for model training are obtained, the text data sets comprise a first text data set and a second text data set, the first text data set comprises a constructed text smoothing task text data set, a text error correction task text data set, a punctuation recovery task text data set and an ITN task text data set, and the second text data set comprises a constructed text smoothing task text data set and a constructed text error correction task text data set; the second text data set is a text data set manually labeled in a real scene; adding a task label for the text data set; and training the first large model by utilizing the text data set added with the task label. According to the embodiment of the invention, the output accuracy of the text obtained by the post-processing task can be improved.

The invention discloses a double-channel voice stream real-time identification method, system and application, and the method comprises the steps: carrying out the preprocessing of collected VOIP call double-channel audio, and maintaining the time sequence synchronization; extracting Mel-frequency cepstral coefficient features and speech spectrogram features of the preprocessed audio, and inputting the spliced features into a Transform deep neural network model for stream speech recognition to obtain a two-way character sequence; generating a unique identifier based on channel identification and voice energy difference, and establishing a corresponding relation with the character sequence; carrying out punctuation prediction and text standardization by utilizing an LSTM-based model, sorting and aligning character sequences according to timestamp fields, and generating a time sequence dialogue stream; and performing anomaly detection and / or storage management on the time sequence dialogue stream to realize real-time quality inspection and agent assistance. According to the invention, synchronous recognition and role distinguishing of double-channel voice are realized, the recognition delay is low, and the recognition accuracy, the detection precision and the real-time performance are high; and high-efficiency management and safety compliance of data are realized by combining distributed encryption storage.

The invention discloses a text-based video automatic production method and device, equipment and a medium, and relates to the technical field of electric data processing. The method comprises the following steps: establishing a video material library and a background music material library; wherein content keywords and corresponding time slice labels are marked on the video materials, and emotion category labels are marked on the background music materials; acquiring an input text, segmenting the input text into a plurality of sentences according to punctuations, respectively performing speech synthesis to generate speech, and recording the audio duration of each sentence; performing keyword matching on each sentence of input text and a video material label to generate a video candidate material set; performing emotion classification on the full text of the input text by using the fine-tuned BERT model, matching emotion types with background music material labels, and generating a background music candidate material set; segmenting the input text according to sentences, and matching audio duration to generate subtitles; and calling the MoviePy library to integrate the video, the voice, the subtitles and the background music, and carrying out accelerated processing by utilizing a GPU to generate the video. Content authenticity and production efficiency are both considered.

The application discloses a speech punctuation detection method, device, equipment, storage medium and program product. The method comprises the following steps: obtaining first speech basic data of a first speech and second speech basic data of a second speech; determining a second silence duration threshold according to the first speech basic data and the second speech basic data; determining a first punctuation detection result of the second speech according to a silence duration of the second speech and the second silence duration threshold, wherein the first punctuation detection result is used for indicating whether the second speech needs to be punctuated. The second speech basic data of the speech that needs to be punctuated and the first speech basic data of the speech that has been punctuated are used to dynamically adjust the silence duration threshold according to the needs, and then the speech punctuation detection is performed according to the second speech basic data and the adjusted silence duration threshold, so that the speech punctuation detection result is obtained, and the accuracy of the speech punctuation detection is improved.

The invention provides a method for automatically labeling work order types on the basis of agents, which comprises the following steps of: performing punctuation standardization processing on an original work order, and converting spoken and non-standardized work order texts into segmented word segments conforming to field specifications in combination with word segmentation in a power field dictionary; unifying and normalizing the segmented word segments through a preset synonym mapping table to obtain a standardized text sequence; the standardized text sequence is input into a bidirectional encoder expression model to output a semantic vector sequence, and deep semantic understanding of the work order text is achieved; related external information is called to be coded into a feature vector, and then the feature vector is fused with the semantic vector sequence through an attention mechanism to generate an enhanced semantic vector; multi-dimensional label prediction tasks are executed in parallel based on a multi-task learning architecture, and multi-class labels and probability distribution are output; the confidence coefficient is obtained by calculating the maximum value of the probability distribution, and the preset process is executed, so that automation and quality management and control of label generation are realized, and the problem of low efficiency of manual power work order processing in the prior art is solved.

This application relates to a punctuation prediction method, content display method, apparatus, device, medium, and product. The method includes: acquiring a set of user texts corresponding to a target punctuation mark, wherein the user texts in the set contain the target punctuation mark; extracting usage preferences for the target punctuation mark from the user texts in the set to obtain usage preference features corresponding to the target punctuation mark; filtering target user texts from the set that match the usage preference features based on the usage preference features; and generating text based on the target user texts to obtain target generated text corresponding to the target punctuation mark. The target user texts and the target generated text are used to train a target punctuation prediction model, which is used to predict punctuation marks in text. This method can improve the accuracy of punctuation prediction.

The invention relates to a real-time punctuation recovery method based on efficient corpus screening. According to the method, firstly, a plurality of open-source Chinese error correction corpus data sets are downloaded, data are cleaned, punctuations are removed, and therefore a simulated voice recognition result is constructed; then mixing a plurality of corpora by using different methods to form a plurality of data sets, and performing data weighting; and finally, comparing the accuracy rates of the prediction results of the plurality of data sets, and continuously changing the generation mode of the data sets according to the recovery effect of the model to finely adjust the model. According to the method, the Chinese error correction corpus and the open-source CT-transformer model are effectively utilized, so that a better experimental result is obtained on the task of speech recognition post-processing. Through the data enhancement method that multiple sentences are spliced into one line, different corpora are mixed according to different proportions, and different punctuations are subjected to data weighting, the problem of real-time punctuation recovery of the corpora after real speech recognition is solved, and the punctuation recovery effect is effectively improved.

The application provides a text punctuation adding method and device, a medium and an electronic equipment. The method comprises the following steps: obtaining a text to be added, performing word segmentation on the text to be added to obtain a plurality of words, obtaining the relationship between the words, obtaining the dependent word of each word and the relationship between each word and its dependent word, determining the relationship vector of each word based on each word, the dependent word of each word and the relationship between each word and its dependent word, obtaining the relationship between the relationship vectors of the plurality of words, and adding punctuation between the plurality of words based on the relationship between the relationship vectors. The relationship between the words in the text to be added and the relationship between the words and the text in the text to be added are considered, and the accuracy of punctuation addition can be improved to a certain extent.

The invention provides a patent document database construction method and device based on technical description. The method comprises the following steps: identifying a main body tag and a description tag of each patent document based on a named entity identification model; carrying out punctuation mark-based feature statement division on the technical description part, and combining all main body tags and / or all description tags belonging to the same feature statement to obtain a technical description combination; and associating the patent number of the patent file with all the technical description combinations to form a patent file database based on the technical description. The patent document is subjected to entity recognition, the feature statements are used as the combination range of the main tags and the description tags, and the technical description of the patent document is combined by using more simplified main information, so that complete coverage of the feature information is realized; and the problem that the retrieval precision is influenced by redundant descriptions or interference words in traditional independent keywords or key sentences is avoided.

1. The name of the design product: the graphical user interface of the semantic content comparison of two documents of an electronic device. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the display interface of the AI intelligent comparison of the differences between two documents. 6. The human-computer interaction mode of the graphical user interface: the front view is the display interface of the comparison of the differences between two documents, and the full-screen view button in the form of four arrows at the top of the interface is clicked to enter the change state diagram, at which time the comparison of the two documents is displayed full screen. 7. Other circumstances that need to be explained: other views are omitted. The "X" in each view represents replaceable or changeable text, numbers, or punctuation marks. The part covered by the gray block in the view belongs to the replaceable or changeable content screen, which does not belong to the content of the design itself.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

A data structure and associated methods for analysis of a continuous 1,197,000-letter unvocalized Hebrew string referred to as the Word of God (WOG). The data structure contains only the twenty-two classical Hebrew letters and their five final forms, with no spacing, punctuation, vowelization, or editorial symbols. Intrinsic placement of the final letters enables deterministic segmentation of the string into 305,490 lexical units and 23,206 verses without external conventions. Fixed letter-number assignments provide a numeric architecture for evaluating substrings, detecting alterations, identifying encoded mathematical correspondences, and performing pattern analysis. The system preserves full semantic range by supporting multiple morphologically valid interpretations of unvocalized Hebrew strings. Methods for segmentation, numeric evaluation, reconstruction, integrity verification, semantic analysis, and mathematical pattern detection are provided thereby providing a reproducible foundation for computational and linguistic research.

1. Name of the product of this design: Graphical user interface for screen saver editing of electronic equipment. 2. Purpose of this design product: for use in an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Purpose of the graphical user interface: Display interface used for editing screen savers. 7. Human-computer interaction method of the graphical user interface: The main view of Design 1 and the main view of Design 2 are screen saver editing interfaces. The screen saver can be changed by sliding the picture at the bottom of the interface left and right. 8. Other situations that require explanation: Omit other views. The “X” in each view represents replaceable or changeable text, numbers or punctuation marks; the portion covered by a gray block in the view belongs to the replaceable or changeable content screen, which does not belong to the content of the design itself for which protection is requested.

1. The name of this design product: Keyboard (EA63). 2. Purpose of the product of this design: A computer input device used to input English letters, Chinese characters, numbers, punctuation marks, etc. into a computer, thereby issuing commands to the computer or inputting data. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: main view.

A system and method guide an Artificial Intelligence engine to determine the semantic and grammatical correctness of a user-expanded sentence in real-time. The sentence validation process involves receiving input from the user, the input includes sentence fragment that the user wishes to expand and user-expanded sentence that the user constructs on the fragment provided. The inputs are broken down into tokens. The word-level tokenization algorithm is used, which identifies tokens by splitting the text into spaces, punctuation marks, and other delimiters. Further, a token comparison algorithm is used to assess the relationship between the sentence fragment and the user-expanded sentence to analyze order and placement. Once the token comparison is complete, a prompt is generated using prompt generator to evaluate grammatical and semantic evaluation of the user-expanded sentence. Real-time feedback is provided to the user based on grammatical and semantic evaluation.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

A punctuation mark delete model learning device is a device that generates, through machine learning, a punctuation mark delete model, and comprises a first learning data generation unit that generates first learning data consisting of a pair of an input sentence including a punctuation mark, a preceding sentence that is a sentence with the punctuation mark assigned at an end of the sentence, and a subsequent sentence following the punctuation mark, and a label indicating whether or not the assignment of the punctuation mark is correct, on the basis of a first text corpus consisting of text obtained by speech recognition processing, and a model learning unit that updates parameters of the punctuation mark delete model on the basis of an error between a probability obtained by inputting the input sentences of the first learning data to the punctuation mark delete model and the label.

The invention relates to an improved key phrase extraction method based on key word screening, the improved key phrase extraction method is suitable for key phrase extraction of a single English patent text, the method is based on an existing KeyBERT technology, a key word screening step is introduced, and the accuracy of key phrase extraction is improved. Performing word segmentation on the patent text, removing stop words and punctuation marks, and extracting key words of the patent text; secondly, generating a key phrase candidate list by utilizing a CountVectorizer function in the KeyBERT, and generating a key phrase candidate list according to the key phrase candidate list; then, screening the candidate key phrases based on strong correlation key words in the field to which the patent text belongs; finally, final key phrases are determined through cosine similarity calculation, and the key word screening step is introduced, so that the number of irrelevant candidate phrases can be effectively reduced, the key phrase extraction precision and efficiency are improved, and the method is particularly suitable for patent text analysis with high technicality and high specialty.

The application provides a regulation voice segmentation method based on speech recognition and endpoint detection, which is applied to air traffic control voice audio stream segmentation, and comprises the following steps: step 1, constructing a punctuation model based on speech recognition and a speech endpoint detection model; step 2, using the punctuation model based on speech recognition to recognize the audio data stream of the regulation voice, and outputting the corresponding text and sentence end identifier of the audio data stream; step 3, using the speech endpoint detection model to judge the speech starting point and ending point contained in the audio data stream of the regulation voice; step 4, segmenting the audio data stream of the regulation voice into audio segments; and step 5, applying the audio segments as data materials to the speech recognition process of the air traffic control system. Through the combination of speech recognition and endpoint detection, the application realizes the automatic segmentation of the air traffic control voice audio stream, and improves the accuracy and efficiency of the segmentation.