CN109741643A - The word processing method of text-oriented big data - Google Patents
The word processing method of text-oriented big data Download PDFInfo
- Publication number
- CN109741643A CN109741643A CN201910032367.4A CN201910032367A CN109741643A CN 109741643 A CN109741643 A CN 109741643A CN 201910032367 A CN201910032367 A CN 201910032367A CN 109741643 A CN109741643 A CN 109741643A
- Authority
- CN
- China
- Prior art keywords
- user
- text
- information
- text information
- age
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Electrically Operated Instructional Devices (AREA)
Abstract
The present invention relates to big data processing fields, in order to solve in existing speech recognition, the identical pronunciation occurred due to areal variation represents the problem of different meanings cause the accuracy of the text information identified to decrease, it provides a kind of word processing method of text-oriented big data, comprising the following steps: obtaining step: obtaining user speech；Processing step: handling the user speech of acquisition, generates text information；It executes step: executing instruction corresponding with text information in database；Wherein: display step: when generating the text information of one or more in processing step, showing all text informations of generation；Matching step: selection information of the user about the text information shown is obtained, and matches text information corresponding with the selection information；After matching text information, instruction corresponding with text information is executed.
Description
Technical field
The present invention relates to big data processing field, specially a kind of word processing method of text-oriented big data.
Background technique
In recent years, the ability that people create data has greatly exceeded the ability for obtaining information, and various data present quick-fried
Fried formula increases.Text is the main carriers of knowledge dissemination and information interchange as most general data type.With speech recognition
The development of technology, now many electronic equipments all have speech identifying function, such as intelligent robot.When user needs intelligent machine
When device people executes a certain function, user can also operate intelligent robot by voice and execute corresponding function.
However, due to the difference of region, although the meaning that identical text represents is also identical, for identical pronunciation generation
The meaning of table is but possible to multifarious.If " street " this word pronounces gai inside many dialects, but " street " is write, this
Sample one, resulting in the sentence finally identified may not be the meaning that user is intended by, and just reduce voice knowledge yet
Other accuracy.
Summary of the invention
The invention is intended to provide a kind of word processing method of text-oriented big data, to solve existing speech recognition
In, the identical pronunciation occurred due to areal variation, which represents the different meanings, has led to the accuracy of the text information identified
The problem of reduction.
The present invention provides base case: the word processing method of text-oriented big data, comprising the following steps:
Obtaining step: user speech is obtained；
Processing step: handling the user speech of acquisition, generates text information；
It executes step: executing instruction corresponding with text information in database；
Further include display step: when generating the text information of one or more in processing step, showing all texts of generation
This information；
Matching step: selection information of the user about the text information shown is obtained, and is matched and the selection information
Corresponding text information；
After matching text information, instruction corresponding with text information is executed；
In processing step, also the age of user and accent are identified；
Judgment step: judge whether user's accent is standard accent, when judging user's accent not is standard accent, is sentenced
It is disconnected whether to carry out language teaching；
Verification step: obtaining the confirmation message of user, if confirmation carries out language teaching, is sentenced according to the user speech got
Whether the age of user that breaks is not more than age threshold；
Teaching procedure: when judging the age of user no more than age threshold, the text information with the user speech is played
The received pronunciation to match；When judging that the age of user is greater than age threshold, the scene selection information of user is obtained, and is played
With the situational dialogues received pronunciation of scene selection information matches.
Illustrate: the standard accent in this programme is native accent and mandarin accent；User's accent is then user locality
Accent, such as ground the A user in the ground B, local at this time is then B, it is local then for A.
The working principle and beneficial effect of this base case is: compared with existing dialogue method: 1. in user speech
After being handled, when the text information that processing obtains is greater than one, that is, indicate to have identified a variety of languages during the treatment
Justice, therefore obtained all text informations can also be shown in this programme, user then can be according to the text shown
Information selection text information identical with oneself user speech of statement, carries out execution step after getting selection information again,
The instruction executed at this time is also to envision with regard to user, that is to say, that is realized in this programme by increasing display step and matching step
Confirmation to the text information that processing obtains, to improve the accuracy of recognition result.
2. in this programme when being identified to voice, other than the text information for identifying the voice, it is contemplated that other places
People is when locally linking up, because the accent of stranger is different from local accent, it is possible that difficult problem is linked up,
Therefore also the accent of user is identified and judgeed in this programme, in the accent and standard accent difference for judging user,
Then illustrate that the user is stranger, when understanding native language it is possible that obstacle, therefore can also confirm at this time to user and be
It is no to need to impart knowledge to students, if the confirmation message received is when being imparted knowledge to students, to carry out teaching procedure, user then passes through broadcasting
Received pronunciation is learnt, thus the language of habit and study native accent, and then user is helped to overcome aphasis, also just keep away
Exempt from the inconvenient problem of life occur because language is different.
3. typically, the age it is small crowd's learning ability it is strong, and age relatively large crowd's learning ability and understanding
Ability is all slightly weaker, therefore in the present solution, also identify to the age of user before being imparted knowledge to students, small for the age
For crowd, in teaching using playing identical with the text information of user speech received pronunciation, that is, native language with
Mandarin Chinese language plays user's word once, and user can be then how to express by the phonetic study native language of broadcasting
's；And for older crowd, learning ability is weakened, if therefore equally using the teaching of the crowd small with the age
Mode, on the one hand, user needs to expend the content that long time could learn all, for another aspect, due to not having needle
Study to property, it is possible to which the content short time for occurring learning is not used, and the content of needs also no do not arrive by study, in this way
One, it cannot also achieve the purpose that teaching, therefore in the present solution, can also obtain when imparting knowledge to students to older crowd
The scene of user selects information, is then imparted knowledge to students according to the scene that user selects, and as user can go to buy vegetables later, therefore selects
The scene bought vegetables, the dialog information that the situation that then can play and buy vegetables at this time matches carries out simulated scenario teaching, to reach
The purpose of using while learning.
Preferred embodiment one: as the preferred of basic scheme, in processing step, when generating the text information of one or more,
Also each text message is numbered and is associated with, shows in step and shows text information and associated number together.
The utility model has the advantages that user only needs to confirm the text in the text information that confirmation is shown after text information is numbered
The number of information, it is easy to operate.
Preferred embodiment two: as the preferred of basic scheme, in processing step, the processing to user speech includes to user's language
Sound carries out text identification after carrying out noise reduction process.The utility model has the advantages that in view of when obtaining user speech, if the environment that user is in
It is more noisy, then the user speech got will contain noise, therefore in this programme when identifying to user speech
Can also noise reduction process be carried out to user speech, to improve the accuracy of the text information of generation.
Preferred embodiment three: as the preferred of basic scheme, in teaching procedure, when judge age of user be greater than age threshold
When, the broadcasting speed for the voice that debases the standard.The utility model has the advantages that in view of for older crowd, playing that word speed is too fast can
The case where user does not understand or do not understand can be will appear, therefore reduced in this programme and play word speed, be conducive to user's study.
Preferred embodiment four: preferably three it is preferred, show step in, text information is amplified into display.It says
It is bright: text information being amplified into display in this programme and is referred in display, the text font size of display increases.The utility model has the advantages that
For older crowd, eyesight can be weak, therefore amplifies text information when showing in this programme and show, is convenient for
User's viewing.
Preferred embodiment five: further including having update step: in the demand information for getting user as the preferred of basic scheme
Afterwards, from the dialog information and storage that acquisition matches with the demand information on internet into database.The utility model has the advantages that considering
Pre-stored dialog information is limited in database, during specifically used it is possible that matching less than with user speech
The dialog information that information matches, therefore it is additionally provided with update step, from internet after the demand information by getting user
On get dialog information after save, to be updated to database, further improve database.
Detailed description of the invention
Fig. 1 is the word processing for the text-oriented big data that the word processing method of text-oriented big data of the present invention uses
The logic diagram of system；
Fig. 2 is the flow chart of the word processing method of text-oriented big data of the present invention.
Specific embodiment
It is further described below by specific embodiment:
Embodiment is substantially as follows:
The word processing method of text-oriented big data, comprising the following steps:
Obtaining step: user speech is obtained；
Processing step: handling the user speech of acquisition, includes to user speech including the processing to user speech
Text identification is carried out after carrying out noise reduction process, generates text information；When generating the text information of one or more, also to each provision
This information is numbered and is associated with；It further include being identified to the age of user and accent；
It executes step: executing instruction corresponding with text information in database；
Display step: when generating the text information of one or more in processing step, showing all text informations of generation,
And text information and associated number are shown together；
Matching step: selection information of the user about the text information shown is obtained, and is matched and the selection information
Corresponding text information；After matching text information, instruction corresponding with text information is executed；
Judgment step: judge whether user's accent is standard accent, when judging user's accent not is standard accent, is sentenced
It is disconnected whether to carry out language teaching；
Verification step: obtaining the confirmation message of user, if confirmation carries out language teaching, is sentenced according to the user speech got
Whether the age of user that breaks is not more than age threshold；
Teaching procedure: when judging the age of user no more than age threshold, the text information with the user speech is played
The received pronunciation to match；When judging that the age of user is greater than age threshold, the scene selection information of user is obtained, and is played
With the situational dialogues received pronunciation of scene selection information matches；When judging that age of user is greater than age threshold, debase the standard
The broadcasting speed of voice；
When judging that the age of user is greater than age threshold, shows in step and text information is amplified into display；
Update step: after getting the demand information of user, acquisition matches with the demand information from internet
Dialog information is simultaneously stored into database.
As shown in Figure 1, additionally providing a kind of word of text-oriented big data in the present embodiment based on above-mentioned processing method
Language processing system, including database, prestore associated text information, dialog information and instruction, are also stored with standard mouth
Sound and age threshold；
Module is obtained, for obtaining the voice messaging of user,
Processing module handles the user speech of acquisition, includes to user speech including the processing to user speech
Text identification is carried out after carrying out noise reduction process, generates text information；When generating the text information of one or more, also to each provision
This information is numbered and is associated with；It further include being identified to the age of user and accent；
Execution module executes instruction corresponding with text information in database；
Display module, when generating the text information of one or more in processing step, display module is used to show generation
All text informations, and text information and associated number are shown together；
Matching module: it for obtaining selection information of the user about the text information shown, and matches and the selection
The corresponding text information of information；After matching text information, execution module executes instruction corresponding with text information；
Judgment module, for judging whether user's accent is identical as the standard accent in database, is judging to use the registered permanent residence
When sound is not standard accent, teaching solicited message is sent to user；The teaching confirmation message that module is also used to obtain user is obtained,
After getting the teaching confirmation message of user, judgment module is also used to judge whether age value is not more than age threshold；
Playing module: when judging the age of user no more than age threshold, the text information with the user speech is played
The received pronunciation to match；When judging that the age of user is greater than age threshold, simulated scenario information is sent to user, obtains mould
Block is also used to obtain the scene selection information of user, and search module matches the situational dialogues to match with scene selection information,
Playing module plays the received pronunciation of the situational dialogues；When playing, playing module is provided with normal playback speed and slow broadcasting
The play mode of speed, when judging that the age of user is greater than age threshold, playing module uses the broadcasting mould of slow broadcasting speed
Formula playing standard voice.
Specific implementation process is as follows:
By taking intelligent domestic robot as an example, the word processing system of the text-oriented big data in the present embodiment is mounted on intelligence
On energy domestic robot, in the prior art, by the way that various application messages are stored in the database of intelligent domestic robot in advance,
User can a series of used dialogues with intelligent domestic robot allow the corresponding task of intelligent domestic robot execution, such as open
It televises specified TV programme, user issues the voice messaging of " playing TV " at this time, obtains module and acquires the voice
Information, processing module generate the text information of " playing TV programme " after being handled, execution module is then according to the text information
Instruction associated with " playing TV programme " is matched from database and is executed, and is opened TV and is played out.
In view of the voice of the crowd of different geographical has local unique accent feature, processing module is to user speech
The text information generated when being handled may have it is a plurality of, if user is when originally meaning " going into the street ", the user speech got
When pronunciation is " shang gai ", the text information generated after processing module processing then by " going into the street ", " being above somebody's turn to do " and is numbered,
Display module shows above-mentioned two text message, is such as shown as " 1- goes into the street " " being somebody's turn to do on 2- ", user then needs back at this time
The selection information of multiple " 1 ", matching module then match instruction corresponding with " going into the street " and are executed from database.
And in view of the voice of the crowd of different geographical has local unique accent feature, crowd's affirmative of other regions
The language of the region can not understood, therefore the crowd of different geographical is when linking up, if carrying out ditch using respectively local language
When logical, it is possible that linking up difficult problem, therefore can also be real by talking with to intelligent domestic robot in the present embodiment
The purpose of existing language teaching, user after study native language by can also overcome due to the different ditches occurred of accent feature
Lead to difficult problem.
Specifically, obtaining module when user and intelligent domestic robot link up and getting user speech, handle mould
Block identifies the user speech, also carries out to the age of user and accent while identifying the text information of user speech
Identification after processing module identifies text information, is completed to play TV by execution module equally by taking " playing TV " as an example
After function, it can also identify that the age value of the user is " X1 " according to the user speech, it is assumed that user for B personage identifies use
User's accent at family is " B accent ", user at this time in A, in database preset standard accent be then " A accent " with
And mandarin accent.It is standard accent that judgment module, which will judge user's accent not, at this point, judgment module can then be sent out to user
Teaching solicited message is sent, such as " whether execute language teaching operation ", when transmission, " whether can be held using to user terminal transmission
The text information or playing module of row language teaching operation " play the voice messaging of " whether executing language teaching operation ", this reality
It applies in example and is carried out in such a way that playing module plays teaching solicited message.
User replys teaching confirmation message, as user feels after receiving teaching solicited message according to their own needs
Oneself is it will be appreciated that native language, and when linking up with native, there is no having to link up difficult problem, oneself is not needed
Language teaching does not need return information then, would not carry out language teaching operation yet.If user feels to need to learn, then may be used
To reply confirmation message of imparting knowledge to students, such as " needs ", after acquisition module gets the teaching confirmation message, then start to execute teaching behaviour
Make.
For comparing older crowd in view of the learning ability of age small crowd, the study energy of age small crowd
Power and understandability are all advantageous, therefore before being imparted knowledge to students, and whether the age value for also judging the user is not more than age threshold
Value.If this identifies that the age value of the user is " X1 ", age threshold is " X ", if " X1 " is not more than " X ", then it represents that the user
Learning ability it is strong, playing module plays identical with the text information of user speech received pronunciation at this time, i.e., plays mould at this time
Block plays " playing TV " using native language and received pronunciation, and user can be then by the phonetic study native language of broadcasting
How to express.
And " if X1 " is greater than " X ", then it represents that the learning ability of the user decreases, at this time to year in the present embodiment
When age big crowd imparts knowledge to students, using simulated scenario teaching method, specifically, when judgment module judgement " X1 " is greater than " X ",
Simulated scenario information is sent to user, if simulated scenario information is " R. S. V. P. needs scene to be simulated ", likewise, sending method
" R. S. V. P. can be played using the text information for sending " R. S. V. P. needs scene to be simulated " to user terminal or by playing module
Need scene to be simulated " voice, the voice of " R. S. V. P. needs scene to be simulated " is played in the present embodiment for playing module, such as
User can go to buy vegetables later, then can reply the scene selection information of " buying vegetables ", obtain module and get scene selection information
Afterwards, for search module after matching situational dialogues associated with " buying vegetables " in database, playing module plays the situational dialogues
Received pronunciation, i.e., after the scene that user selects " buying vegetables ", playing module can be played and buy vegetables the dialogue letter that situation matches
Breath carries out simulated scenario teaching, to achieve the purpose that using while learning.
What has been described above is only an embodiment of the present invention, and the common sense such as well known specific structure and characteristic are not made herein in scheme
Excessive description, technical field that the present invention belongs to is all before one skilled in the art know the applying date or priority date
Ordinary technical knowledge can know the prior art all in the field, and have using routine experiment hand before the date
The ability of section, one skilled in the art can improve and be implemented in conjunction with self-ability under the enlightenment that the application provides
This programme, some typical known features or known method should not become one skilled in the art and implement the application
Obstacle.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, can also make
Several modifications and improvements out, these also should be considered as protection scope of the present invention, these all will not influence the effect that the present invention is implemented
Fruit and patent practicability.The scope of protection required by this application should be based on the content of the claims, the tool in specification
The records such as body embodiment can be used for explaining the content of claim.
Claims (6)
1. the word processing method of text-oriented big data, comprising the following steps:
Obtaining step: user speech is obtained；
Processing step: handling the user speech of acquisition, generates text information；
It executes step: executing instruction corresponding with the text information in database；
It is characterized by also including display steps: when generating the text information of one or more in processing step, showing generation
All text informations；
Matching step: selection information of the user about the text information shown is obtained, and is matched opposite with the selection information
The text information answered；
After matching text information, instruction corresponding with the text information is executed；
In the processing step, also the age of user and accent are identified；
Judgment step: judge whether user's accent is standard accent, and when judging user's accent not is standard accent, judgement is
No carry out language teaching；
Verification step: obtaining the confirmation message of user, should according to the user speech judgement got if confirmation carries out language teaching
Whether age of user is not more than age threshold；
Teaching procedure: when judging the age of user no more than age threshold, the text information phase with the user speech is played
The received pronunciation matched；When judging that the age of user is greater than age threshold, the scene selection information of user is obtained, and plays and is somebody's turn to do
The situational dialogues received pronunciation of scene selection information matches.
2. the word processing method of text-oriented big data according to claim 1, it is characterised in that: the processing step
In, when generating the text information of one or more, also each text message is numbered and is associated with, shown text in step
Information is shown together with associated number.
3. the word processing method of text-oriented big data according to claim 1, it is characterised in that: the processing step
In, the processing to user speech includes carrying out text identification after carrying out noise reduction process to user speech.
4. the word processing method of text-oriented big data according to claim 1, it is characterised in that: the teaching procedure
In, when judging that age of user is greater than age threshold, the broadcasting speed for the voice that debases the standard.
5. the word processing method of text-oriented big data according to claim 4, it is characterised in that: the display step
In, text information is amplified into display.
6. the word processing method of text-oriented big data according to claim 1, it is characterised in that: further include having update
Step: after getting the demand information of user, the dialog information to match with the demand information is obtained from internet and is deposited
It stores up in database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910032367.4A CN109741643A (en) | 2019-01-14 | 2019-01-14 | The word processing method of text-oriented big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910032367.4A CN109741643A (en) | 2019-01-14 | 2019-01-14 | The word processing method of text-oriented big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109741643A true CN109741643A (en) | 2019-05-10 |
Family
ID=66364712
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910032367.4A Pending CN109741643A (en) | 2019-01-14 | 2019-01-14 | The word processing method of text-oriented big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109741643A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112330998A (en) * | 2020-11-18 | 2021-02-05 | 托普爱英(北京)科技有限公司 | Learning support method and learning support device |
| CN113381922A (en) * | 2020-03-09 | 2021-09-10 | 阿尔派株式会社 | Electronic device and information reproduction control method |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064070A (en) * | 2006-04-26 | 2007-10-31 | 杭州草莓资讯有限公司 | Interactive intelligent type language teaching doll |
| CN101938391A (en) * | 2010-08-31 | 2011-01-05 | 中山大学 | Voice processing method, system, remote controller, set-top box and cloud server |
| CN102834842A (en) * | 2010-03-23 | 2012-12-19 | 诺基亚公司 | Method and apparatus for determining a user age range |
| CN103344973A (en) * | 2013-06-24 | 2013-10-09 | 开平市中铝实业有限公司 | Auto voice input navigation system |
| CN103730032A (en) * | 2012-10-12 | 2014-04-16 | 李志刚 | Method and system for controlling multimedia data |
| CN204904612U (en) * | 2015-07-29 | 2015-12-23 | 嘉兴市莱沃机器人科技有限公司 | Human -like teaching machine people |
| CN105374356A (en) * | 2014-08-29 | 2016-03-02 | 株式会社理光 | Speech recognition method, speech assessment method, speech recognition system, and speech assessment system |
| CN106200886A (en) * | 2015-04-30 | 2016-12-07 | 包伯瑜 | A kind of intelligent movable toy manipulated alternately based on language and toy using method |
| CN107067833A (en) * | 2017-02-15 | 2017-08-18 | 山东顺势教育科技有限公司 | A kind of speech recognition and evaluation system |
| CN107644643A (en) * | 2017-09-27 | 2018-01-30 | 安徽硕威智能科技有限公司 | A kind of voice interactive system and method |
| CN107924642A (en) * | 2015-04-05 | 2018-04-17 | 斯米拉布莱斯有限公司 | The learning Content of customization is presented to infant based on the developmental age |
| CN108235813A (en) * | 2017-02-28 | 2018-06-29 | 华为技术有限公司 | The method and relevant device of a kind of phonetic entry |
-
2019
- 2019-01-14 CN CN201910032367.4A patent/CN109741643A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101064070A (en) * | 2006-04-26 | 2007-10-31 | 杭州草莓资讯有限公司 | Interactive intelligent type language teaching doll |
| CN102834842A (en) * | 2010-03-23 | 2012-12-19 | 诺基亚公司 | Method and apparatus for determining a user age range |
| CN101938391A (en) * | 2010-08-31 | 2011-01-05 | 中山大学 | Voice processing method, system, remote controller, set-top box and cloud server |
| CN103730032A (en) * | 2012-10-12 | 2014-04-16 | 李志刚 | Method and system for controlling multimedia data |
| CN103344973A (en) * | 2013-06-24 | 2013-10-09 | 开平市中铝实业有限公司 | Auto voice input navigation system |
| CN105374356A (en) * | 2014-08-29 | 2016-03-02 | 株式会社理光 | Speech recognition method, speech assessment method, speech recognition system, and speech assessment system |
| CN107924642A (en) * | 2015-04-05 | 2018-04-17 | 斯米拉布莱斯有限公司 | The learning Content of customization is presented to infant based on the developmental age |
| CN106200886A (en) * | 2015-04-30 | 2016-12-07 | 包伯瑜 | A kind of intelligent movable toy manipulated alternately based on language and toy using method |
| CN204904612U (en) * | 2015-07-29 | 2015-12-23 | 嘉兴市莱沃机器人科技有限公司 | Human -like teaching machine people |
| CN107067833A (en) * | 2017-02-15 | 2017-08-18 | 山东顺势教育科技有限公司 | A kind of speech recognition and evaluation system |
| CN108235813A (en) * | 2017-02-28 | 2018-06-29 | 华为技术有限公司 | The method and relevant device of a kind of phonetic entry |
| CN107644643A (en) * | 2017-09-27 | 2018-01-30 | 安徽硕威智能科技有限公司 | A kind of voice interactive system and method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113381922A (en) * | 2020-03-09 | 2021-09-10 | 阿尔派株式会社 | Electronic device and information reproduction control method |
| CN113381922B (en) * | 2020-03-09 | 2024-02-27 | 阿尔派株式会社 | Electronic device and information reproduction control method |
| CN112330998A (en) * | 2020-11-18 | 2021-02-05 | 托普爱英(北京)科技有限公司 | Learning support method and learning support device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Andreas et al. | Reasoning about pragmatics with neural listeners and speakers | |
| Everett | Linguistic relativity: Evidence across languages and cognitive domains | |
| CN109074345A (en) | Course is automatically generated and presented by digital media content extraction | |
| CN101551947A (en) | Computer system for assisting spoken language learning | |
| KR102654480B1 (en) | Knowledge based dialogue system and method for language learning | |
| CN111833853A (en) | Voice processing method and device, electronic equipment and computer readable storage medium | |
| CN106486121A (en) | It is applied to the voice-optimizing method and device of intelligent robot | |
| CN106847279A (en) | Man-machine interaction method based on robot operating system ROS | |
| CN109326162A (en) | A kind of spoken language exercise method for automatically evaluating and device | |
| CN109493658A (en) | Situated human-computer dialogue formula spoken language interactive learning method | |
| Picca et al. | Natural Language Processing in Serious Games: A state of the art. | |
| CN110415725A (en) | Use the method and system of first language data assessment second language pronunciation quality | |
| CN109741643A (en) | The word processing method of text-oriented big data | |
| Wagner et al. | Applying cooperative machine learning to speed up the annotation of social signals in large multi-modal corpora | |
| CN109741744A (en) | AI robot dialog control method and system based on big data search | |
| Himmelmann | Prosody in language documentation | |
| CN113177114A (en) | Natural language semantic understanding method based on deep learning | |
| Saunders et al. | Towards using prosody to scaffold lexical meaning in robots | |
| Wang | Research on open oral English scoring system based on neural network | |
| CN109473007B (en) | English natural spelling teaching method and system combining phonemes with sound side | |
| Saunders et al. | Robot acquisition of lexical meaning-moving towards the two-word stage | |
| Krasnova et al. | The use of speech technology in computer assisted language learning systems | |
| Lee et al. | Foreign language tutoring in oral conversations using spoken dialog systems | |
| KR102292477B1 (en) | Server and method for automatic assessment of oral language proficiency | |
| CN108717854A (en) | Method for distinguishing speek person based on optimization GFCC characteristic parameters |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190510 |