CN110705220B - Text editing method, device and system applied to intelligent voice mouse and storage medium - Google Patents
Text editing method, device and system applied to intelligent voice mouse and storage medium Download PDFInfo
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- CN110705220B CN110705220B CN201910923013.9A CN201910923013A CN110705220B CN 110705220 B CN110705220 B CN 110705220B CN 201910923013 A CN201910923013 A CN 201910923013A CN 110705220 B CN110705220 B CN 110705220B
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Abstract
The invention relates to the field of data processing, in particular to a text editing method, a device, a system and a storage medium applied to an intelligent voice mouse, wherein the method comprises the following steps: firstly, acquiring a user voice instruction, collecting and arranging, then, carrying out natural language processing on collected and arranged data through syntactic analysis, using MITIE as a tool for feature extraction and entity identification to extract features of the processed data, next, using sklearn as a tool for intention judgment, finally obtaining the intention of the user instruction, and finally, matching with functions of a corresponding editor according to the intention of the obtained user instruction and carrying out corresponding text editing operation.
Description
Technical Field
The invention relates to the field of data processing, in particular to a text editing method, device and system applied to an intelligent voice mouse and a storage medium.
Background
At present, a mode of editing a text by people mainly performs manual operation, such as clicking corresponding function keys by a mouse or performing corresponding operation by adopting shortcut keys of a keyboard, but many people unfamiliar with office software may not smoothly perform the operation required by the people, and although a mainstream interaction mode is a key mouse and a touch screen, a trend of replacing a traditional interaction mode by a voice interaction mode has appeared. In fact, in life, we are increasingly using voice interactions. When driving, we get more and more used to give various instructions to the smart phone or the system through voice, the voice assistant has good completion degree to our commands, and the smart sound box which is gradually popularized is popular with more and more people. As technology advances, the manner in which voice interactions penetrate into more devices, we have been influenced by the manner in which voice interactions and unknowingly added, but we have not been self-aware, as not all changes can be easily perceived. It can be determined that future humans will apply to voice interaction technology in richer scenarios, and voice interaction will have a wider market. In this way, the voice interaction does not only not become a "chicken rib", but may also become the first interaction means in the future.
At present, the voice interaction technology is already applied to various fields, but development and utilization in the office field are relatively few, so the invention develops a text editing method applied to an intelligent voice mouse to expand the application of intelligent voice interaction in the office field.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to develop a text editing method applied to an intelligent voice mouse, so that people edit texts more intelligently and conveniently, and the invention provides the text editing method applied to the intelligent voice mouse, which comprises the following steps of:
step S1: acquiring and arranging the acquired user voice instruction;
step S2: carrying out natural language processing on the collected and arranged data through syntactic analysis;
step S3: extracting data features using MITIE as a tool for feature extraction and entity recognition;
step S4: using sklearn as a tool for determining the intention, and finally obtaining the intention of the user instruction;
step S5: the intention of the user instruction obtained through the last module is matched with the function of the corresponding editor, and corresponding text editing operation is performed.
Specifically, the natural language processing in step S2 includes the following steps:
step S21: chinese word segmentation: the open source system of Chinese word segmentation algorithm based on CRF, namely conditional random field, segments a Chinese character sequence into individual words;
step S22: part of speech tagging, namely using an HMM (hidden Markov model) and a Viterbi algorithm, and a maximum entropy algorithm to tag the part of speech of a word;
step S23: the method comprises the steps of marking a special name, and identifying an entity with a specific meaning in a text by adopting a standard HMM model and a Viterbi algorithm, wherein the entity mainly comprises a person name, a place name, an organization name and a proper noun;
step S24: semantic chunk, which adopts CRF, namely conditional random field to carry out semantic chunk;
step S25: syntax analysis, automatically deducing the grammar structure of a sentence according to a given grammar system, analyzing grammar units contained in the sentence and the relation between the grammar units, and converting the sentence into a structured grammar tree;
step S26: deep layer analysis: the method comprises the steps of syntactic relation deconstructing analysis, text similarity analysis, text keyword extraction, text classification, content abstract and emotion tendency analysis, wherein the text classification adopts a naive Bayesian algorithm.
Preferably, the parsing in step S25 includes phrase structure parsing and dependency parsing.
In order to achieve the above object, the present invention further provides a text editing apparatus for an intelligent voice mouse, comprising
The user command picking module is used for acquiring user voice commands and collecting and arranging the voice commands;
the instruction processing module is used for carrying out natural language processing on the collected and tidied data;
the feature extraction module is used for extracting features of the processed data by using MITIE as a tool for feature extraction and entity identification;
the acquisition module uses sklearn as a tool for judging the intention, and finally obtains the intention of the user instruction;
and the execution module is used for matching the obtained intention of the user instruction with the function of the corresponding editor and carrying out corresponding text editing operation.
The invention also provides a text editing system applied to the intelligent voice mouse, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the method when executing the computer program.
To achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a computer program, the processor implementing the steps of the above method when executing the computer program.
The invention has the beneficial effects that:
the text editing method applied to the intelligent voice mouse is designed, a user can edit the text through voice interaction, replaces manual operation before, edits the text in a voice interaction mode, can greatly save the operation time of the user, and improves the office efficiency of the user.
Drawings
Fig. 1 is a flowchart of a text editing method applied to an intelligent voice mouse according to embodiment 1 of the present invention.
Fig. 2 is a block diagram of a text editing apparatus applied to an intelligent voice mouse according to embodiment 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Fig. 1 is a flowchart of a text editing method applied to an intelligent voice mouse according to an embodiment 1. As shown in fig. 1, a text editing method applied to an intelligent voice mouse includes the following steps:
step S1: and acquiring and arranging the acquired user voice instruction.
Step S2: and carrying out natural language processing on the collected and collated data through syntactic analysis.
In the step, chinese word segmentation is firstly carried out, and a Chinese character sequence is segmented into individual words by an open source system of a Chinese word segmentation algorithm based on a Conditional Random Field (CRF); then, marking the part of speech of the word by using an HMM (hidden Markov model) +Viterbi algorithm and a maximum entropy algorithm; then, identifying entities with specific meanings in the text by adopting a standard HMM model and a Viterbi algorithm, wherein the entities mainly comprise a person name, a place name, an organization name and proper nouns; then, semantic chunk is performed based on a Conditional Random Field (CRF) method; then, carrying out syntactic analysis including phrase structure syntactic analysis and dependency syntactic analysis, automatically deducing the syntactic structure of the sentence according to a given syntactic system, analyzing the syntactic units contained in the sentence and the relation between the syntactic units, and converting the sentence into a structured syntactic tree; and finally, carrying out deep analysis, and carrying out analysis comprising analysis of syntactic relation deconstruction, analysis of text similarity, extraction of text keywords, text classification, content abstract and emotion tendency analysis, wherein the text classification adopts a naive Bayesian algorithm.
Step S3: data features are extracted using MITIE as a tool for feature extraction and entity recognition.
Step S4: using sklearn as a tool for determining intention, and finally obtaining the intention of the user instruction.
Step S5: the intention of the user instruction obtained through the last module is matched with the function of the corresponding editor, and corresponding text editing operation is performed.
Example 2
Fig. 2 is a block diagram of a text editing apparatus for an intelligent voice mouse according to embodiment 2 of the present invention. As shown in fig. 2, the present embodiment provides a text editing apparatus for an intelligent voice mouse, including
The user command picking module is used for acquiring user voice commands and collecting and arranging the voice commands;
the instruction processing module is used for carrying out natural language processing on the collected and tidied data;
the feature extraction module is used for extracting features of the processed data by using MITIE as a tool for feature extraction and entity identification;
the acquisition module uses sklearn as a tool for judging the intention, and finally obtains the intention of the user instruction;
and the execution module is used for matching the obtained intention of the user instruction with the function of the corresponding editor and carrying out corresponding text editing operation.
Example 3
The embodiment provides a text editing system applied to an intelligent voice mouse, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the method when executing the computer program.
Example 4
The present embodiment provides a computer readable storage medium having stored thereon a computer program, the processor implementing the steps of the above method when executing the computer program.
In summary, the text editing method, device, system and storage medium applied to the intelligent voice mouse disclosed in the embodiments of the present invention designs a text editing method applied to the intelligent voice mouse, and a user can implement editing of text through voice interaction, so as to replace the previous manual operation, thereby greatly saving the operation time of the user and improving the office efficiency of the user.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any modifications and substitutions will be apparent to those skilled in the art within the scope of the present invention, and it is intended that the scope of the present invention shall be defined by the appended claims.
Claims (5)
1. The text editing method applied to the intelligent voice mouse is characterized by comprising the following steps of:
step S1: acquiring and arranging the acquired user voice instruction;
step S2: the collected and consolidated data is processed in natural language through syntactic analysis, and the method comprises the following steps:
step S21: chinese word segmentation: the open source system of Chinese word segmentation algorithm based on CRF, namely conditional random field, segments a Chinese character sequence into individual words;
step S22: part of speech tagging, namely using an HMM (hidden Markov model) and a Viterbi algorithm, and a maximum entropy algorithm to tag the part of speech of a word;
step S23: the method comprises the steps of marking a special name, and identifying an entity with a specific meaning in a text by adopting a standard HMM model and a Viterbi algorithm, wherein the entity mainly comprises a person name, a place name, an organization name and a proper noun;
step S24: semantic chunk, which adopts CRF, namely conditional random field to carry out semantic chunk;
step S25: syntax analysis, automatically deducing the grammar structure of a sentence according to a given grammar system, analyzing grammar units contained in the sentence and the relation between the grammar units, and converting the sentence into a structured grammar tree;
step S26: deep layer analysis: performing syntactic relation deconstructing analysis, text similarity analysis, text keyword extraction, text classification, content abstract and emotion tendency analysis, wherein the text classification adopts a naive Bayesian algorithm;
step S3: extracting data features using MITIE as a tool for feature extraction and entity recognition;
step S4: using sklearn as a tool for determining the intention, and finally obtaining the intention of the user instruction;
step S5: the intention of the user instruction obtained through the last module is matched with the function of the corresponding editor, and corresponding text editing operation is performed.
2. The text editing method applied to an intelligent voice mouse as claimed in claim 1, wherein: the syntactic analysis in step S2 includes phrase structure parsing and dependency parsing.
3. A text editing device applied to an intelligent voice mouse is characterized in that: comprising
The user command picking module is used for acquiring user voice commands and collecting and arranging the voice commands;
the instruction processing module is used for carrying out natural language processing on the collected and tidied data;
the feature extraction module is used for extracting features of the processed data by using MITIE as a tool for feature extraction and entity identification;
the acquisition module uses sklearn as a tool for judging the intention, and finally obtains the intention of the user instruction;
the execution module is used for matching the obtained intention of the user instruction with the function of the corresponding editor and carrying out corresponding text editing operation;
the natural language processing includes the steps of:
chinese word segmentation: the open source system of Chinese word segmentation algorithm based on CRF, namely conditional random field, segments a Chinese character sequence into individual words;
part of speech tagging, namely using an HMM (hidden Markov model) and a Viterbi algorithm, and a maximum entropy algorithm to tag the part of speech of a word;
the method comprises the steps of marking a special name, and identifying an entity with a specific meaning in a text by adopting a standard HMM model and a Viterbi algorithm, wherein the entity mainly comprises a person name, a place name, an organization name and a proper noun;
semantic chunk, which adopts CRF, namely conditional random field to carry out semantic chunk;
syntax analysis, automatically deducing the grammar structure of a sentence according to a given grammar system, analyzing grammar units contained in the sentence and the relation between the grammar units, and converting the sentence into a structured grammar tree;
deep layer analysis: the method comprises the steps of syntactic relation deconstructing analysis, text similarity analysis, text keyword extraction, text classification, content abstract and emotion tendency analysis, wherein the text classification adopts a naive Bayesian algorithm.
4. A text editing system for an intelligent voice mouse comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that: the processor, when executing the computer program, implements the steps of the method of any of the preceding claims 1 or 2.
5. A computer-readable storage medium having stored thereon a computer program, characterized by: the program when executed by a processor performs the steps of the method of any of the preceding claims 1 or 2.
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