CN110334253A - A kind of furniture control method and device - Google Patents
A kind of furniture control method and device Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
- G06F16/90344—Query processing by using string matching techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
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- G—PHYSICS
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2642—Domotique, domestic, home control, automation, smart house
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The embodiment of the invention provides a kind of furniture control method and devices, wherein a kind of furniture control method includes: acquisition voice messaging；The voice messaging is converted to text information；The text information is split using default word segmentation regulation to obtain several initial words；The control instruction of inquiry and the initial word matched in default furniture control library；The control instruction is executed to the furniture.After voice messaging is carried out speech analysis according to preset method for splitting, is inquired in the furniture control library with big data and be accurately controlled instruction, realize the intelligent control of furniture.
Description
Technical field
The present invention relates to intelligentized Furniture technical fields, more particularly to a kind of furniture control method and a kind of furniture control dress
It sets.
Background technique
Currently, many intelligentized Furniture and intelligent appliance, be all by intelligent sound box realization technology, by speech recognition,
And it is converted into text, realize the control of sound equipment.
Intelligent sound identification equipment is all then to carry out voice using speech synthesis to be converted into text, but have targetedly
Furniture control technology is not strong, and fitment order executes confusion, causes equipment operability not strong.
Existing intelligent appliance is all independent single-item, intelligentized Furniture and intelligent appliance separate type, puts everywhere, unsightly,
Pickup effect difference etc..
Summary of the invention
In view of the above problems, it proposes the embodiment of the present invention and overcomes the above problem or at least partly in order to provide one kind
A kind of furniture control method to solve the above problems and a kind of corresponding furniture control device.
To solve the above-mentioned problems, the embodiment of the invention discloses a kind of furniture control methods, comprising:
Acquire voice messaging；
The voice messaging is converted to text information；
The text information is split using default word segmentation regulation to obtain several initial words；
The control instruction of inquiry and the initial word matched in default furniture control library；
The control instruction is executed to the furniture.
Further, described that the text information is split to obtain several initial words using default word segmentation regulation
Step, comprising:
Segmenting method based on string matching searches furniture control library one by one, to the text information into fractionation,
Obtain several initial words.
Further, the segmenting method based on string matching searches furniture control library one by one, to the text
This information is into fractionation, the step of obtaining several initial words, comprising:
Using one of Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and minimum syncopation
Or a variety of methods split the text information, obtain several initial words.
Further, described the step of inquiring the control instruction with the initial word matched in default furniture control library
Later, comprising:
The importance of the initial word is labeled, training data is obtained；
The training data is stored in furniture control library.
The embodiment of the invention discloses a kind of furniture control devices, comprising:
Voice acquisition module, for acquiring voice messaging；
Voice conversion module, for the voice messaging to be converted to text information；
Semantic module, for being split to obtain several initial lists to the text information using default word segmentation regulation
Word；
Instructions match module, the control instruction for inquiry and the initial word matched in default furniture control library；
Control module, for executing the control instruction to the furniture.
Further, the semantic module includes:
Semantic analysis submodule searches furniture control library for the segmenting method based on string matching one by one, right
The text information obtains several initial words into fractionation.
Further, the semantic analysis submodule includes:
Semantic analysis unit, for using Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and most
One of small syncopation or a variety of methods split the text information, obtain several initial words.
Further, described instruction matching module includes:
Training submodule, is labeled for the importance to the initial word, obtains training data；
Sub-module stored, for the training data to be stored in furniture control library.
The embodiment of the invention discloses a kind of electronic equipment, including processor, memory and it is stored on the memory
And the computer program that can be run on the processor, the computer program are realized above-mentioned when being executed by the processor
Furniture control method the step of.
The embodiment of the invention discloses a kind of computer readable storage medium, stored on the computer readable storage medium
The step of computer program, the computer program realizes above-mentioned furniture control method when being executed by processor.
The embodiment of the present invention includes following advantages: by acquisition voice messaging, voice messaging is converted to text information, it is right
Text information is split according to default word segmentation regulation, obtains several initial words, is inquired in default furniture control library and first
The control instruction that beginning word matches executes above-mentioned control instruction to furniture, by voice messaging according to preset method for splitting into
After row speech analysis, is inquired in the furniture control library with big data and be accurately controlled instruction, realize the intelligence control of furniture
System.
Detailed description of the invention
Fig. 1 is a kind of step flow chart of furniture control method embodiment of the invention；
Fig. 2 is a kind of structural block diagram of furniture control device embodiment of the invention.
Specific embodiment
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
One of the core concepts of the embodiments of the present invention is, by acquiring voice messaging, voice messaging is converted to text
Information splits text information according to default word segmentation regulation, obtains several initial words, controls Ku Neicha in default furniture
The control instruction to match with initial word is ask, above-mentioned control instruction is executed to furniture, by voice messaging according to preset fractionation
After method carries out speech analysis, is inquired in the furniture control library with big data and be accurately controlled instruction, realize furniture
Intelligent control.
Referring to Fig.1, a kind of step flow chart of furniture control method embodiment of the invention is shown, can specifically include
Following steps:
S1 acquires voice messaging；
In the present embodiment, the acquisition of voice messaging is carried out directly in fitment using microphone matrix, and is carried out
Integrate laggard Row noise Processing for removing.Above-mentioned microphone matrix, which refers to by multiple pick-up points, collects initial speech information, then
A part of ambient noise is filtered by special algorithm, improves the quality of call.
The voice messaging is converted to text information by S2；
In the present embodiment, after the voice messaging obtained to above-mentioned microphone matrix is handled, to above-mentioned voice messaging
Text conversion is carried out, text information is converted thereof into.
S3 splits the text information using default word segmentation regulation to obtain several initial words；
In the present embodiment, using local furniture library, cloud furniture library and the household electrical appliances vocabulary annotation repository of profession, above-mentioned text
This information is syncopated as matching all possible word, then determines optimal cutting as a result, also with statistical language model
It is to be utilized viterbi algorithm (viterbi) using sequence labelling (sequence labeling) problem in natural language processing
It can complete mark to infer, to obtain word segmentation result.Sequence labelling (sequence labeling) is more than classification meaning
Add an extensive task, the information content that object for needing to classify itself can be provided classification task is considerably less, more
Information is derived from context, and context determines the mark classification of existing object, such as word sense disambiguation, can go this word
In the case where falling, the meaning of a word is made inferences by context.Viterbi algorithm is a kind of dynamic programming algorithm, is most had for finding
There may be-Viterbi path-hidden state the sequences of observed events sequence, especially in Markoff information source context and
In hidden Markov model.Dynamic programming algorithm can be used to find most probable context-free in statistical moment theory
Derivation (parsing) character string, referred to as " Viterbi analysis ".
S4, the control instruction of inquiry and the initial word matched in default furniture control library；Appointed by construction sentence
The language model that the server of business decomposes draws term vector, can be really fully next to predict using all information above
A word obtains core word, keyword extraction, obtains user accurately semantic analysis and personal intention.
S5 executes the control instruction to the furniture.
In this embodiment, the intention control instruction of user similar in the voice messaging issued with user is directly returned to intelligence
Furniture and household electrical appliance terminal simultaneously are implemented to be precisely controlled.
In the present embodiment, described that the text information is split to obtain several initial lists using default word segmentation regulation
The step of word, comprising:
S31, the segmenting method based on string matching search furniture control library one by one, to the text information into tearing open
Point, obtain several initial words.
In the present embodiment, Chinese word is the molecular basic unit of sentence, unlike English sentence has divided word, in
The first step of the text-processing of text is exactly that Chinese text information splits (participle), faces three big basic problems in participle: 1, segmenting
Specification, 2, segmentation ambiguity, 3, the identification of unregistered word.Chinese Word Automatic Segmentation is probably divided into two major classes, and one kind is based on character string
Matched segmenting method, i.e. scanning character string, if it find that the substring of character string is identical with word, even if matching.This kind of participle is logical
Some heuristic rules, such as " matching of forwards/reverse maximum ", the strategies such as " priority of long word " can often be added.Segmenting method speed
Degree is fast, is all O (n) time complexity, realizes simple.
In the present embodiment, the segmenting method based on string matching searches furniture control library one by one, to institute
The step of text information is stated into fractionation, obtains several initial words, comprising:
S301, using in Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and minimum syncopation
One or more methods split the text information, obtain several initial words.In the present embodiment, pass through by
Text information is syncopated as individual character string, is then compared with dictionary, just records if it is a word, otherwise by increase or
Person reduce an individual character, continue to compare, there remains an individual character always and then terminate, if the individual character string can not cutting, conduct
It is not logged in processing, the word that maximum matches must assure that next scanning is not that the prefix of the word or word in vocabulary can just be tied
Beam.Wherein, Forward Maximum Method method refers to and from left to right matches several continuation characters wait segment in text with vocabulary, if
It matches, is then syncopated as a word.Reversed maximum matching method is often referred to simply as RMM method, since the end of text processed
With scanning, the 2i character (i word word string) of least significant end is taken to remove matching field if it fails to match as matching field every time
One word of foremost, continues to match.Correspondingly, the dictionary for word segmentation that it is used is backward dictionary, and each entry therein will
Mode is stored in reverse order.In actual treatment, document is first subjected to the processing of falling row, reverse order document is generated, then, according to backward word
Allusion quotation handles reverse order document Forward Maximum Method method.Two-way maximum matching method refers to primary, reverse using positive cutting
Cutting is primary, just chooses if cutting result twice is the same identical as a result, abiding by most if cutting result is different twice
More fewer, better principle chooses final cutting result to the monosyllabic word not having in big matching principle and dictionary.
In the present embodiment, inquiry and the control instruction of the initial word matched in default furniture control library
After step, comprising:
S41 is labeled the importance of the initial word, obtains training data；
In the present embodiment, the participle mode based on statistics and machine learning, which is the word based on mark
Property and statistical nature, Chinese is modeled, i.e., model parameter is estimated according to the data (corpus marked) that observe
Meter is trained.The participle stage pass through again model calculate it is various participle occur probability, using the word segmentation result of maximum probability as
Final result.Common sequence labelling model has hidden Markov model and condition random field.Hidden Markov model (Hidden
Markov Model, HMM) it is statistical model, it is used to describe the Markov process containing implicit unknown parameter, from can
The implicit parameter of the process is determined in the parameter of observation.Condition random field (conditional random field
Algorithm, CRF) it is a kind of based on the probability graph model for following Markov property.The method of machine learning can be handled very well
Ambiguity and unregistered word problem.
The training data is stored in furniture control library by S42.
In the present embodiment, because of the classification task of machine learning, supervised learning, training data, autonomous use are carried out
Training data from extract method, using program from search log in automatic mining.Extraction is implied in massive logs data
User is labeled the importance of each keyword, and obtained training data will integrate " annotation results " of hundred million grades of users,
Covering surface is wider, and from actual search data, the object set distribution of training result and mark is close, and training data is more smart
Really, preferably to reaching more preferable instruction control effect under furniture and household electrical appliances.
In another embodiment, offline semantics recognition and semantic analysis are supported, the sequence mark in natural language processing is used
Remember (sequence labeling) problem, utilizes hidden Markov model (HMM) in usual way, maximum entropy model
(MAXENT), maximum entropy Markov model (MEMM), condition random field (CRF) etc. predict the mark of each word of text string, into
Row deep learning, thus allow intelligentized Furniture and household electrical appliances more understand people need to manipulate at present which type of instruction, allow furniture or
The instruction of household electrical appliances is more in line with human nature and precision increases, strong real-time.
It should be noted that for simple description, therefore, it is stated as a series of action groups for embodiment of the method
It closes, but those skilled in the art should understand that, embodiment of that present invention are not limited by the describe sequence of actions, because according to
According to the embodiment of the present invention, some steps may be performed in other sequences or simultaneously.Secondly, those skilled in the art also should
Know, the embodiments described in the specification are all preferred embodiments, and the related movement not necessarily present invention is implemented
Necessary to example.
Referring to Fig. 2, show a kind of structural block diagram of furniture control device embodiment of the invention, can specifically include as
Lower module:
Voice acquisition module 1, for acquiring voice messaging；
Voice conversion module 2, for the voice messaging to be converted to text information；
Semantic module 3, it is several initial for being split to obtain to the text information using default word segmentation regulation
Word；
Instructions match module 4, the control instruction for inquiry and the initial word matched in default furniture control library；
Control module 4, for executing the control instruction to the furniture.
In the present embodiment, voice acquisition module is made of speech chip and two microphones (Microphone, MIC),
Double MIC and four MIC etc. are mainly used for noise elimination, and speech chip is connected using I2S bus with micro-control unit, I2S
(Inter-IC Sound) bus, also known as integrated circuit built-in audio bus are that the audio data between digital audio-frequency apparatus passes
A kind of defeated bus standard, dedicated for data transmission and various multimedia systems between audio frequency apparatus, it is used the bus
Along the design of independent wire transmission clock and data-signal, by avoiding data and clock signal separation because of the time difference
The distortion of induction saves the expense that the professional equipment of audio jitter is resisted in purchase for user.Micro-control unit
(Microcontroller Unit；MCU), also known as one chip microcomputer (Single Chip Microcomputer) or
Single-chip microcontroller is central processing unit (Central Process Unit；CPU frequency and specification) does appropriate reduction, and will be interior
Deposit the perimeter interfaces such as (memory), counter (Timer), USB, A/D conversion, UART, PLC, DMA or even LCD driving circuit all
Integration on a single chip, forms the computer of chip-scale, does various combination control for different applications.
In the present embodiment, the semantic module 3 includes:
Semantic analysis submodule searches furniture control library for the segmenting method based on string matching one by one, right
The text information obtains several initial words into fractionation.
The semantic analysis submodule includes:
Semantic analysis unit, for using Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and most
One of small syncopation or a variety of methods split the text information, obtain several initial words.
Described instruction matching module 4 includes:
Training submodule, is labeled for the importance to the initial word, obtains training data；
Sub-module stored, for the training data to be stored in furniture control library.
The invention also discloses a kind of electronic equipment, including processor, memory and it is stored on the memory and energy
Enough computer programs run on the processor, the computer program realize above-mentioned family when being executed by the processor
Has the step of control method.
The invention also discloses a kind of computer readable storage medium, stores and calculate on the computer readable storage medium
The step of machine program, the computer program realizes above-mentioned furniture control method when being executed by processor.
For device embodiment, since it is basically similar to the method embodiment, related so being described relatively simple
Place illustrates referring to the part of embodiment of the method.
All the embodiments in this specification are described in a progressive manner, the highlights of each of the examples are with
The difference of other embodiments, the same or similar parts between the embodiments can be referred to each other.
It should be understood by those skilled in the art that, the embodiment of the embodiment of the present invention can provide as method, apparatus or calculate
Machine program product.Therefore, the embodiment of the present invention can be used complete hardware embodiment, complete software embodiment or combine software and
The form of the embodiment of hardware aspect.Moreover, the embodiment of the present invention can be used one or more wherein include computer can
With in the computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) of program code
The form of the computer program product of implementation.
The embodiment of the present invention be referring to according to the method for the embodiment of the present invention, terminal device (system) and computer program
The flowchart and/or the block diagram of product describes.It should be understood that flowchart and/or the block diagram can be realized by computer program instructions
In each flow and/or block and flowchart and/or the block diagram in process and/or box combination.It can provide these
Computer program instructions are set to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing terminals
Standby processor is to generate a machine, so that being held by the processor of computer or other programmable data processing terminal devices
Capable instruction generates for realizing in one or more flows of the flowchart and/or one or more blocks of the block diagram
The device of specified function.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing terminal devices
In computer-readable memory operate in a specific manner, so that instruction stored in the computer readable memory generates packet
The manufacture of command device is included, which realizes in one side of one or more flows of the flowchart and/or block diagram
The function of being specified in frame or multiple boxes.
These computer program instructions can also be loaded into computer or other programmable data processing terminal devices, so that
Series of operation steps are executed on computer or other programmable terminal equipments to generate computer implemented processing, thus
The instruction executed on computer or other programmable terminal equipments is provided for realizing in one or more flows of the flowchart
And/or in one or more blocks of the block diagram specify function the step of.
Although the preferred embodiment of the embodiment of the present invention has been described, once a person skilled in the art knows bases
This creative concept, then additional changes and modifications can be made to these embodiments.So the following claims are intended to be interpreted as
Including preferred embodiment and fall into all change and modification of range of embodiment of the invention.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or terminal device including a series of elements not only wrap
Those elements are included, but also including other elements that are not explicitly listed, or further includes for this process, method, article
Or the element that terminal device is intrinsic.In the absence of more restrictions, being wanted by what sentence "including a ..." limited
Element, it is not excluded that there is also other identical elements in process, method, article or the terminal device for including the element.
Above to a kind of furniture control method provided by the present invention and a kind of furniture control device, detailed Jie has been carried out
It continues, used herein a specific example illustrates the principle and implementation of the invention, and the explanation of above embodiments is only
It is to be used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, according to this hair
Bright thought, there will be changes in the specific implementation manner and application range, in conclusion the content of the present specification should not manage
Solution is limitation of the present invention.
Claims (10)
1. a kind of furniture control method characterized by comprising
Acquire voice messaging；
The voice messaging is converted to text information；
The text information is split using default word segmentation regulation to obtain several initial words；
The control instruction of inquiry and the initial word matched in default furniture control library；
The control instruction is executed to the furniture.
2. the method according to claim 1, wherein it is described using default word segmentation regulation to the text information into
Row splits the step of obtaining several initial words, comprising:
Segmenting method based on string matching is searched furniture control library one by one and is obtained to the text information into fractionation
Several initial words.
3. according to the method described in claim 2, it is characterized in that, the segmenting method based on string matching is searched one by one
The furniture controls library, to the text information into fractionation, the step of obtaining several initial words, comprising:
Using one of Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and minimum syncopation or more
Kind method splits the text information, obtains several initial words.
4. the method according to claim 1, wherein the inquiry in default furniture control library with it is described initial
After the step of control instruction of word matched, comprising:
The importance of the initial word is labeled, training data is obtained；
The training data is stored in furniture control library.
5. a kind of furniture control device characterized by comprising
Voice acquisition module, for acquiring voice messaging；
Voice conversion module, for the voice messaging to be converted to text information；
Semantic module, for being split to obtain several initial words to the text information using default word segmentation regulation；
Instructions match module, the control instruction for inquiry and the initial word matched in default furniture control library；
Control module, for executing the control instruction to the furniture.
6. device according to claim 5, which is characterized in that the semantic module includes:
Semantic analysis submodule searches furniture control library for the segmenting method based on string matching, to described one by one
Text information obtains several initial words into fractionation.
7. device according to claim 6, which is characterized in that the semantic analysis submodule includes:
Semantic analysis unit, for being cut using Forward Maximum Method method, reversed maximum matching method, two-way maximum matching method and minimum
One of point-score or a variety of methods split the text information, obtain several initial words.
8. device according to claim 5, which is characterized in that described instruction matching module includes:
Training submodule, is labeled for the importance to the initial word, obtains training data；
Sub-module stored, for the training data to be stored in furniture control library.
9. electronic equipment, which is characterized in that including processor, memory and be stored on the memory and can be at the place
The computer program run on reason device is realized when the computer program is executed by the processor as appointed in Claims 1-4
The step of furniture control method described in one.
10. computer readable storage medium, which is characterized in that computer program is stored on the computer readable storage medium,
The computer program realizes the step of furniture control method according to any one of claims 1 to 4 when being executed by processor
Suddenly.
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| CN201910502850.4A CN110334253A (en) | 2019-06-11 | 2019-06-11 | A kind of furniture control method and device |
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| CN (1) | CN110334253A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113707141A (en) * | 2021-08-10 | 2021-11-26 | 大唐南京发电厂 | Voice control method and voice control system of DCS (distributed control system) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20030034443A (en) * | 2001-10-23 | 2003-05-09 | 삼성전자주식회사 | Apparatus and method for controlling a user interface having a voice recognition function |
| CN1674540A (en) * | 2004-03-25 | 2005-09-28 | 联想(北京)有限公司 | Method for central controlling home appliances based on home appliances control center |
| CN103197571A (en) * | 2013-03-15 | 2013-07-10 | 张春鹏 | Control method, device and system |
| CN106571140A (en) * | 2016-11-14 | 2017-04-19 | Tcl集团股份有限公司 | Electrical appliance intelligent control method based on voice meaning and electrical appliance intelligent control system thereof |
| CN106886161A (en) * | 2015-12-16 | 2017-06-23 | 美的集团股份有限公司 | The control method of audio amplifier, system and audio amplifier |
-
2019
- 2019-06-11 CN CN201910502850.4A patent/CN110334253A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20030034443A (en) * | 2001-10-23 | 2003-05-09 | 삼성전자주식회사 | Apparatus and method for controlling a user interface having a voice recognition function |
| CN1674540A (en) * | 2004-03-25 | 2005-09-28 | 联想(北京)有限公司 | Method for central controlling home appliances based on home appliances control center |
| CN103197571A (en) * | 2013-03-15 | 2013-07-10 | 张春鹏 | Control method, device and system |
| CN106886161A (en) * | 2015-12-16 | 2017-06-23 | 美的集团股份有限公司 | The control method of audio amplifier, system and audio amplifier |
| CN106571140A (en) * | 2016-11-14 | 2017-04-19 | Tcl集团股份有限公司 | Electrical appliance intelligent control method based on voice meaning and electrical appliance intelligent control system thereof |
Non-Patent Citations (2)
| Title |
|---|
| 杨秀樟等: "《Python 网络数据爬取及分析从入门到精通 分析篇》", 30 June 2018 * |
| 郑艳群等: "《对外汉语计算机辅助教学的理论研究》", 31 July 2006 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113707141A (en) * | 2021-08-10 | 2021-11-26 | 大唐南京发电厂 | Voice control method and voice control system of DCS (distributed control system) |
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