CN109255048A - A kind of music storage and extraction system based on big data - Google Patents
A kind of music storage and extraction system based on big data Download PDFInfo
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Abstract
The present invention discloses a kind of music storage and extraction system based on big data, including memory space division module, music storing data library, music preprocessing module, music extraction module and Cloud Server, memory space division module is connect with music storing data library, and Cloud Server is connect with music storing data library, music preprocessing module and music extraction module respectively.The present invention is divided by memory space of the memory space division module to storage music, convenient for regularly being stored to different genres of music, improves the logic of storage；Pass through the happy preprocessing module of Cloud Server union synaeresis and music extraction module, the music that need to be stored is carried out matching degree of conformity coefficient with each storing sub-units and is stored to the matching highest storing sub-units of degree of conformity coefficient, and the high music of keyword match satisfaction is counted by input screening keyword, convenient for being stored and being extracted to music, have the characteristics that storage is high and accurate high with extraction efficiency.
Description
Technical field
The invention belongs to music storages and extractive technique field, are related to a kind of music storage and extraction based on big data
System.
Background technique
With the continuous development of society, the stress of people and life stress gradually increase, and music can be effectively
The stress of people is reduced, different music types often brings the different effect of people, and music mainly has following effect: 1. sounds
Pleasure can promote the happiness of people: listen to music more, you can be allowed to be easier to possess happiness, especially when your mood well
When, concert enhances your so happy sense, makes you happier；2 music can allow people tranquil: suitable music is selected,
It listens quietly, the mood that you can be allowed impetuous, irritated slowly becomes tranquil, and people many times needs handle newly to become quiet, ability
Preferably go thinking thing；3. music allows people to loosen: people can be helped to loosen body now with many music, it is some light
Music can play good effect, and people can also preferably fall asleep after loosening, and sleep more steady and sure, listen music, then
Cooperate and deeply breathes, it can be more preferable；4. music allow people closer to: when doing group activity, we can usually use a first song
As starting or terminating, it is emotion and information because of music transmitting, people can be allowed to empathize, when everybody choruses a first song
When, it often has and apparent feels the feeling to keep together.
As music categories are higher and higher, for music during storage, it is chaotic storage easily occur, be not easy to music according to
Regular condition is stored, and the difficulty to music management is increased, and there is storage logic difference and storage efficiency is low
Problem, meanwhile, music there is a problem of screening accuracy difference, in order to solve problem above, now design one during extraction
Music storage and extraction system of the kind based on big data.
Summary of the invention
The purpose of the present invention is to provide it is a kind of based on big data music storage and extraction system, solve existing sound
During happy storage and extraction, there are problems that storing poor logic, low efficiency and screening poor accuracy.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of music storage and extraction system based on big data, including memory space division module, music storing data
Library, music preprocessing module, music extraction module and Cloud Server, memory space division module and music storing data library connect
It connects, Cloud Server is connect with music storing data library, music preprocessing module and music extraction module respectively；
Memory space division module is divided into several storages for dividing to the memory space in music storing data library
The identical storage unit in space, different storage units store different music types, several deposit are divided into same storage unit
The identical sub- storage unit in space is stored up, several sub- storage units in storage unit are used to store the difference under same music type
Emotional category；
Music storing data library is stored for storing to the music of the different emotions classification under different music types
There are the music keyword and music melody of the different emotions classification under different music types, the different emotions under different music types
The music of classification is stored in each storing sub-units in storage unit and mutually corresponds, to different music types according to every class song
Sum sequence from high to low is successively ranked up, and respectively 1,2 ..., k ..., x do not sympathize with according in all music types
Feel song sum corresponding to type to be ranked up according to sequence from high to low, respectively 1,2 ..., g ..., y, not unisonance
Different lyrics keyword and standard tune are equipped in different emotions classification under happy type, it is same under different music types
Keyword in emotional category constitutes set of keywords Akg(akg1,akg2,...,akgi,...,akgN), akgI is expressed as k-th
I-th of keyword in g-th of emotional category under music type, the standard in same emotional category under different music types
Tune constitutes tune data set Bkg(bkg1,bkg2,...,bkgj,...,bkgM), bkgJ is expressed as under k-th of music type
J-th of standard tune in g-th of emotional category；
The music that music preprocessing module is used to treat storage carries out the extraction of music melody and the music lyrics, to music
Tune is divided according to tune play time sequencing with constant duration T, and the tune after division constitutes music melody set C
(c1, c2 ..., cv ..., cf), cv is expressed as tune of the music to be stored within v-th of period, and presses to the music lyrics
It is divided according to the chronological order of music with constant duration T, the music lyrics after division constitute music wordbook
It closes D (d1, d2 ..., dv ..., df), dv is expressed as the lyrics of the music to be stored within v-th of time, speech preprocessing module
The music melody set of the music to be stored of extraction and music lyrics set are sent to Cloud Server；
Cloud Server receives the music melody set and music wordbook for the music to be stored that music preprocessing module is sent
Close, and by the lyrics in each period in received music lyrics set B respectively with each storing sub-units in each storage unit
In set of keywords in all keywords compared one by one, obtain the period lyrics comparison set A 'kgv(a′kgv1,
a′kgv2,...,a′kgvi,...,a′kgvN), a 'kgvI is expressed as i-th in g-th of emotional category under k-th of music type
The reduced value that keyword and all lyrics of the music to be stored within v-th of period compare, if under k-th of music type
G-th of emotional category in i-th of standard tune occur in the music melody in v-th of period of music to be stored,
Then take a 'kgvI is equal to 1, otherwise, takes a 'kgvI is equal to 0；
Meanwhile Cloud Server by the tune in each period in music melody set C respectively with it is each in each storage unit
Tune data set B in storing sub-unitskgIn standard tune compare, obtain period tune comparison set B 'kgv
(b′kgv1,b′kgv2,...,b′kgvj,...,b′kgvM), b 'kgvJ is expressed as in g-th of emotional category under k-th of music type
Reduced value between the music melody in v-th of period of j-th of standard tune and music to be stored, if k-th of music class
J-th of standard tune in g-th of emotional category under type goes out in the music melody in v-th of period of music to be stored
It is existing, then take b 'kgvJ is equal to 1, otherwise, takes b 'kgvJ is equal to 0；
Period lyrics comparison of the Cloud Server according to song to be stored in each period is gathered and period tune pair
Than set, and specific gravity shared by each keyword is combined, counts of each storing sub-units in song to be stored and each storage unit
With degree of conformity coefficient, highest storage of matching degree of conformity coefficient for filtering out the song to be stored and each storing sub-units is single
Member, and the song to be stored is stored to the matching highest storing sub-units of degree of conformity coefficient；
Music extraction module is used to input several keywords of music to be extracted, and several keywords of input are constituted screening
Set of keywords E (e1, e2 ..., eh), and each keyword screened in set of keywords is input to Cloud Server, receive cloud
The music of screening server, and carry out the output of music；
Cloud Server receives the screening set of keywords that music extraction module is sent, and will screen the pass in set of keywords
The music lyrics stored in key word and each storing sub-units in each storage unit compare, and obtain screening keyword comparison set
E′kgt(e′kgt1,e′kgt2,...,e′kgtH), E 'kgtEach emotion being expressed as under set of keywords to be screened and each music type
The lyrics reduced value of t-th of song under classification, e 'kgtH be expressed as screening set of keywords in h-th of keyword in each music
Whether the lyrics of t-th of song under each emotional category under type occur, if h-th of keyword exists in screening set of keywords
Exist in t-th of song under each emotional category under each music type, then e 'kgtH is equal to 1, otherwise, takes 0, and count screening
The number that keyword occurs in the music lyrics obtains screening keyword number set SE 'kgt(se′kgt1,se′kgt2,...,
se′kgtH), se 'kgtH is expressed as under each emotional category in screening set of keywords under h-th of keyword and each music type
T-th of song corresponds to the number occurred in the lyrics；
Cloud Server counts the music lyrics stored in each storage unit according to the screening keyword of input and screening is crucial
Word matches the highest song of satisfaction coefficient, and the matching highest song of satisfaction coefficient is extracted, and is sent to music and mentions
Modulus block.
Further, the music type includes video display song, TV song, animation song, nursery rhymes song, national song
Song, light music song, rock song, country song, lied, jazz songs.
Further, the emotional category includes sentimental class, passion class, light class, quiet class, happy class, happy class, treats
Hurt class and misses class.
Further, the corresponding specific gravity of different keywords under each music type in each emotional category is different, respectively
gakg1,gakg2,...,gakgi,...,gakgN, and gakg1+gakg2+...+gakgi+...+gakgN=1.
Further, the matching degree of conformity coefficient formulas is
gakgI is specific gravity shared by i-th of keyword in g-th of emotional category under k-th of music type, a 'kgvI is expressed as kth
I-th of keyword and all songs of the music to be stored within v-th of period in g-th of emotional category under a music type
The reduced value that word compares, b 'kgvJ is expressed as j-th of standard tune in g-th of emotional category under k-th of music type
With reduced value of the music to be stored between the music melody in v-th of period.
Further, the calculation formula of the keyword match satisfaction coefficient is
e′kgtH is expressed as t-th of song in screening set of keywords under each emotional category of h-th of keyword under each music type
The lyrics whether occur, if occur, value 1, otherwise, value 0, se 'kgtH is expressed as h in screening set of keywords
The number occurred in a keyword lyrics corresponding with t-th of song under each emotional category under each music type.
Beneficial effects of the present invention:
Music storage and extraction system provided by the invention based on big data, by memory space division module to storage
The memory space of music is divided, and convenient for regularly being stored to different genres of music, improves the logic of storage；
By Cloud Server and music preprocessing module, the lyrics are reconciled to the music march that need to be stored and are divided, and tune distinguished each
In storage unit the corresponding tune of each storing sub-units compare and the lyrics respectively with respectively storage is single in each storage unit
The corresponding keyword of member compares, with count the matching degree of conformity coefficient of music to be stored and each storing sub-units and store to
It matches in the highest storing sub-units of degree of conformity coefficient, has the characteristics that storage efficiency is high and accuracy is high, meanwhile, pass through sound
Happy extraction module simultaneously combines Cloud Server, filters out the high music of keyword match satisfaction, which is convenient for carrying out music
Storage and extraction have the characteristics that storage is high and accurate high with extraction efficiency.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will be described below to embodiment required
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is a kind of schematic diagram of music storage and extraction system based on big data of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Refering to Figure 1, a kind of music storage and extraction system based on big data, including memory space divide mould
Block, music storing data library, music preprocessing module, music extraction module and Cloud Server, memory space division module and sound
Happy storing data library connection, Cloud Server connect with music storing data library, music preprocessing module and music extraction module respectively
It connects；
Memory space division module is divided into several storages for dividing to the memory space in music storing data library
The identical storage unit in space, different storage units store different music types, several deposit are divided into same storage unit
The identical sub- storage unit in space is stored up, several sub- storage units in storage unit are used to store the difference under same music type
Emotional category；
Music storing data library is stored for storing to the music of the different emotions classification under different music types
There are the music keyword and music melody of the different emotions classification under different music types, the different emotions under different music types
The music of classification is stored in each storing sub-units in storage unit and mutually corresponds, the music type include video display song,
TV song, animation song, nursery rhymes song, ethnic song, light music song, rock song, country song, lied,
Jazz songs etc. are successively ranked up different music types according to the sequence of every class song sum from high to low, respectively
1,2 ..., k ..., x, the emotional category include sentimental class, passion class, light class, quiet class, happy class, happy class, treat
Hurt class and miss class, according to song sum corresponding to different emotions type in all music types according to sequence from high to low
It is ranked up, respectively 1,2 ..., g ..., y, is closed in the different emotions classification under different music types equipped with the different lyrics
Key word and standard tune, the keyword in same emotional category under different music types constitute set of keywords Akg(akg1,
akg2,...,akgi,...,akgN), akgI is expressed as i-th of keyword in g-th of emotional category under k-th of music type,
And the corresponding specific gravity of difference keyword is different, respectively gakg1,gakg2,...,gakgi,...,gakgN, and gakg1+gakg2
+...+gakgi+...+gakgN=1, the standard tune in same emotional category under different music types constitute tune data collection
Close Bkg(bkg1,bkg2,...,bkgj,...,bkgM), bkgJ is expressed as in g-th of emotional category under k-th of music type
J standard tune.
The music that music preprocessing module is used to treat storage carries out the extraction of music melody and the music lyrics, to music
Tune is divided according to tune play time sequencing with constant duration T, and the tune after division constitutes music melody set C
(c1, c2 ..., cv ..., cf), cv is expressed as tune of the music to be stored within v-th of period, and presses to the music lyrics
It is divided according to the chronological order of music with constant duration T, the music lyrics after division constitute music wordbook
It closes D (d1, d2 ..., dv ..., df), dv is expressed as the lyrics of the music to be stored within v-th of time, speech preprocessing module
The music melody set of the music to be stored of extraction and music lyrics set are sent to Cloud Server；
Cloud Server receives the music melody set and music wordbook for the music to be stored that music preprocessing module is sent
Close, and by the lyrics in each period in received music lyrics set B respectively with each storing sub-units in each storage unit
In set of keywords in all keywords compared one by one, obtain the period lyrics comparison set A 'kgv(a′kgv1,
a′kgv2,...,a′kgvi,...,a′kgvN), a 'kgvI is expressed as i-th in g-th of emotional category under k-th of music type
The reduced value that keyword and all lyrics of the music to be stored within v-th of period compare, if under k-th of music type
G-th of emotional category in i-th of standard tune occur in the music melody in v-th of period of music to be stored,
Then take a 'kgvI is equal to 1, otherwise, takes a 'kgvI is equal to 0；
Meanwhile Cloud Server by the tune in each period in music melody set C respectively with it is each in each storage unit
Tune data set B in storing sub-unitskgIn standard tune compare, obtain period tune comparison set B 'kgv
(b′kgv1,b′kgv2,...,b′kgvj,...,b′kgvM), b 'kgvJ is expressed as in g-th of emotional category under k-th of music type
Reduced value between the music melody in v-th of period of j-th of standard tune and music to be stored, if k-th of music class
J-th of standard tune in g-th of emotional category under type goes out in the music melody in v-th of period of music to be stored
It is existing, then take b 'kgvJ is equal to 1, otherwise, takes b 'kgvJ is equal to 0；
Period lyrics comparison of the Cloud Server according to song to be stored in each period is gathered and period tune pair
Than set, and specific gravity shared by each keyword is combined, counts of each storing sub-units in song to be stored and each storage unit
With degree of conformity coefficient, the matching degree of conformity coefficient formulas is
gakgI is specific gravity shared by i-th of keyword in g-th of emotional category under k-th of music type, a 'kgvI is expressed as kth
I-th of keyword and all songs of the music to be stored within v-th of period in g-th of emotional category under a music type
The reduced value that word compares, b 'kgvJ is expressed as j-th of standard tune in g-th of emotional category under k-th of music type
With reduced value of the music to be stored between the music melody in v-th of period, the song to be stored and each storage are filtered out
The highest storing sub-units of matching degree of conformity coefficient of unit, and the song to be stored is stored to matching degree of conformity coefficient highest
Storing sub-units；
Music extraction module is used to input several keywords of music to be extracted, and several keywords of input are constituted screening
Set of keywords E (e1, e2 ..., eh), and each keyword screened in set of keywords is input to Cloud Server, receive cloud
The music of screening server, and carry out the output of music；
Cloud Server receives the screening set of keywords that music extraction module is sent, and will screen the pass in set of keywords
The music lyrics stored in key word and each storing sub-units in each storage unit compare, and obtain screening keyword comparison set
E′kgt(e′kgt1,e′kgt2,...,e′kgtH), E 'kgtEach emotion being expressed as under set of keywords to be screened and each music type
The lyrics reduced value of t-th of song under classification, e 'kgtH be expressed as screening set of keywords in h-th of keyword in each music
Whether the lyrics of t-th of song under each emotional category under type occur, if h-th of keyword exists in screening set of keywords
Exist in t-th of song under each emotional category under each music type, then e 'kgtH is equal to 1, otherwise, takes 0, and count screening
The number that keyword occurs in the music lyrics obtains screening keyword number set SE 'kgt(se′kgt1,se′kgt2,...,
se′kgtH), se 'kgtH is expressed as under each emotional category in screening set of keywords under h-th of keyword and each music type
T-th of song corresponds to the number occurred in the lyrics.
Cloud Server counts the music lyrics stored in each storage unit according to the screening keyword of input and screening is crucial
Word matches the highest song of satisfaction coefficient, and the matching highest song of satisfaction coefficient is extracted, and is sent to music and mentions
Modulus block, wherein the calculation formula of keyword match satisfaction coefficient is
e′kgtH is expressed as t-th of song in screening set of keywords under each emotional category of h-th of keyword under each music type
The lyrics whether occur, if occur, value 1, otherwise, value 0, se 'kgtH is expressed as h in screening set of keywords
The number occurred in a keyword lyrics corresponding with t-th of song under each emotional category under each music type.
Music storage and extraction system provided by the invention based on big data, by memory space division module to storage
The memory space of music is divided, and convenient for regularly being stored to different genres of music, improves the logic of storage；
By Cloud Server and music preprocessing module, the lyrics are reconciled to the music march that need to be stored and are divided, and tune distinguished each
In storage unit the corresponding tune of each storing sub-units compare and the lyrics respectively with respectively storage is single in each storage unit
The corresponding keyword of member compares, with count the matching degree of conformity coefficient of music to be stored and each storing sub-units and store to
It matches in the highest storing sub-units of degree of conformity coefficient, has the characteristics that storage efficiency is high and accuracy is high, meanwhile, pass through sound
Happy extraction module simultaneously combines Cloud Server, filters out the high music of keyword match satisfaction, which is convenient for carrying out music
Storage and extraction have the characteristics that storage is high and accurate high with extraction efficiency.
The above content is just an example and description of the concept of the present invention, affiliated those skilled in the art
It makes various modifications or additions to the described embodiments or is substituted in a similar manner, without departing from invention
Design or beyond the scope defined by this claim, be within the scope of protection of the invention.
Claims (6)
1. a kind of music storage and extraction system based on big data, it is characterised in that: including memory space division module, music
Storing data library, music preprocessing module, music extraction module and Cloud Server, memory space division module and music store number
It is connected according to library, Cloud Server is connect with music storing data library, music preprocessing module and music extraction module respectively；
Memory space division module is divided into several memory spaces for dividing to the memory space in music storing data library
Identical storage unit, different storage units store different music types, and it is empty that several storages are divided into same storage unit
Between identical sub- storage unit, several sub- storage units in storage unit are used to store the different emotions under same music type
Classification；
Music storing data library is stored with not for storing to the music of the different emotions classification under different music types
Different emotions classification with the music keyword and music melody of the different emotions classification under music type, under different music types
Music be stored in each storing sub-units in storage unit and mutually correspond, to different music types according to every class song sum
Sequence from high to low is successively ranked up, and respectively 1,2 ..., k ..., x, according to different emotions class in all music types
Song sum corresponding to type is ranked up according to sequence from high to low, and respectively 1,2 ..., g ..., y, different music classes
Different lyrics keyword and standard tune, the same emotion under different music types are equipped in different emotions classification under type
Keyword in classification constitutes set of keywords Akg(akg1,akg2,...,akgi,...,akgN), akgI is expressed as k-th of music
I-th of keyword in g-th of emotional category under type, the standard tune in same emotional category under different music types
Constitute tune data set Bkg(bkg1,bkg2,...,bkgj,...,bkgM), bkgJ is expressed as g-th under k-th of music type
J-th of standard tune in emotional category；
The music that music preprocessing module is used to treat storage carries out the extraction of music melody and the music lyrics, presses to music melody
Divided according to tune play time sequencing with constant duration T, tune after division constitute music melody set C (c1,
C2 ..., cv ..., cf), cv is expressed as tune of the music to be stored within v-th of period, and to the music lyrics according to sound
The happy chronological order played is divided with constant duration T, and the music lyrics after division constitute music lyrics set D
(d1, d2 ..., dv ..., df), dv are expressed as the lyrics of the music to be stored within v-th of time, and speech preprocessing module will
The music melody set and music lyrics set for the music to be stored extracted are sent to Cloud Server；
Cloud Server receives the music melody set and music lyrics set for the music to be stored that music preprocessing module is sent, and
By the lyrics in each period in received music lyrics set B respectively with the pass in each storing sub-units in each storage unit
All keywords in key word set are compared one by one, obtain period lyrics comparison set A 'kgv(a′kgv1,a′kgv2,...,a′kgvi,...,a′kgvN), a 'kgvI is expressed as i-th of pass in g-th of emotional category under k-th of music type
The reduced value that key word and all lyrics of the music to be stored within v-th of period compare, if under k-th of music type
I-th of standard tune in g-th of emotional category occurs in the music melody in v-th of period of music to be stored, then
Take a 'kgvI is equal to 1, otherwise, takes a 'kgvI is equal to 0；
Meanwhile Cloud Server by the tune in each period in music melody set C respectively with respectively stored in each storage unit
Tune data set B in subelementkgIn standard tune compare, obtain period tune comparison set B 'kgv(b′kgv1,b′kgv2,...,b′kgvj,...,b′kgvM), b 'kgvJ is expressed as in g-th of emotional category under k-th of music type
The reduced value of j-th of standard tune and music to be stored between the music melody in v-th of period, if k-th of music type
Under g-th of emotional category in j-th of standard tune in the music melody in v-th of period of music to be stored go out
It is existing, then take b 'kgvJ is equal to 1, otherwise, takes b 'kgvJ is equal to 0；
Cloud Server collects according to song to be stored in the period lyrics comparison set of each period and the comparison of period tune
It closes, and combines specific gravity shared by each keyword, count the matching symbol of each storing sub-units in song to be stored and each storage unit
Right coefficient filters out the highest storing sub-units of matching degree of conformity coefficient of the song to be stored Yu each storing sub-units, and
The song to be stored is stored to the matching highest storing sub-units of degree of conformity coefficient；
Music extraction module is used to input several keywords of music to be extracted, and it is crucial that several keywords of input are constituted screening
Word set E (e1, e2 ..., eh), and each keyword screened in set of keywords is input to Cloud Server, receive cloud service
The music of device screening, and carry out the output of music；
Cloud Server receives the screening set of keywords that music extraction module is sent, and will screen the keyword in set of keywords
It is compared with the music lyrics stored in storing sub-units each in each storage unit, obtains screening keyword comparison set E 'kgt
(e′kgt1,e′kgt2,...,e′kgtH), E 'kgtEach emotional category being expressed as under set of keywords to be screened and each music type
Under t-th of song lyrics reduced value, e 'kgtH be expressed as screening set of keywords in h-th of keyword in each music type
Under each emotional category under the lyrics of t-th of song whether occur, if h-th of keyword is in each sound in screening set of keywords
Exist in t-th of song under each emotional category under happy type, then e 'kgtH is equal to 1, otherwise, takes 0, and it is crucial to count screening
The number that word occurs in the music lyrics obtains screening keyword number set SE 'kgt(se′kgt1,se′kgt2,...,se′kgtH), se 'kgtH is expressed as the t under each emotional category in screening set of keywords under h-th of keyword and each music type
A song corresponds to the number occurred in the lyrics；
Cloud Server counts the music lyrics stored in each storage unit and screening keyword according to the screening keyword of input
It is extracted with the highest song of satisfaction coefficient, and by the matching highest song of satisfaction coefficient, is sent to music and extracts mould
Block.
2. a kind of music storage and extraction system based on big data according to claim 1, it is characterised in that: the sound
Happy type include video display song, TV song, animation song, nursery rhymes song, ethnic song, light music song, rock song,
Country song, lied, jazz songs.
3. a kind of music storage and extraction system based on big data according to claim 1, it is characterised in that: the feelings
Sense classification includes sentimental class, passion class, light class, quiet class, happy class, happy class, class of curing the wound and misses class.
4. a kind of music storage and extraction system based on big data according to claim 1, it is characterised in that: each music
The corresponding specific gravity of different keywords under type in each emotional category is different, respectively gakg1,gakg2,...,gakgi,...,
gakgN, and gakg1+gakg2+...+gakgi+...+gakgN=1.
5. a kind of music storage and extraction system based on big data according to claim 1, it is characterised in that: described
It is with degree of conformity coefficient formulasgakgI is
Specific gravity shared by i-th of keyword in g-th of emotional category under k-th of music type, a 'kgvI is expressed as k-th of music
All lyrics of i-th of keyword and music to be stored within v-th of period in g-th of emotional category under type carry out
The reduced value of comparison, b 'kgvJ be expressed as j-th of standard tune in g-th of emotional category under k-th of music type with wait deposit
Store up reduced value of the music between the music melody in v-th of period.
6. a kind of music storage and extraction system based on big data according to claim 1, it is characterised in that: the pass
Key word matching satisfaction coefficient calculation formula bee′kgtH table
It is shown as the lyrics of t-th of song in screening set of keywords under each emotional category of h-th of keyword under each music type
Whether occur, if occurring, value 1, otherwise, and value 0, se 'kgtH is expressed as h-th of key in screening set of keywords
The number occurred in the word lyrics corresponding with t-th of song under each emotional category under each music type.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110134825A (en) * | 2019-05-15 | 2019-08-16 | 黄瑞阳 | Music retrieval method and device |
| CN110188161A (en) * | 2019-06-04 | 2019-08-30 | 广德元瑞生产力促进中心有限公司 | A kind of enterprise information technology achievement assessment system based on big data |
| CN112294329A (en) * | 2020-10-23 | 2021-02-02 | 青岛黄海学院 | Psychological monitoring system and method based on music emotion recognition |
| CN113613023A (en) * | 2021-10-08 | 2021-11-05 | 中通服建设有限公司 | Intelligent eye monitoring system based on cloud network fusion |
-
2018
- 2018-09-17 CN CN201811083892.0A patent/CN109255048A/en not_active Withdrawn
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110134825A (en) * | 2019-05-15 | 2019-08-16 | 黄瑞阳 | Music retrieval method and device |
| CN110188161A (en) * | 2019-06-04 | 2019-08-30 | 广德元瑞生产力促进中心有限公司 | A kind of enterprise information technology achievement assessment system based on big data |
| CN112294329A (en) * | 2020-10-23 | 2021-02-02 | 青岛黄海学院 | Psychological monitoring system and method based on music emotion recognition |
| CN112294329B (en) * | 2020-10-23 | 2023-02-21 | 青岛黄海学院 | Psychological monitoring system and method based on music emotion recognition |
| CN113613023A (en) * | 2021-10-08 | 2021-11-05 | 中通服建设有限公司 | Intelligent eye monitoring system based on cloud network fusion |
| CN113613023B (en) * | 2021-10-08 | 2021-12-17 | 中通服建设有限公司 | Intelligent eye monitoring system based on cloud network fusion |
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