The document discusses a survey on music recognition searching applications, finding that while users appreciate the convenience of such apps, limitations include over half refusing to help enlarge databases and the top reason for not using an app being required fees, suggesting challenges in building large databases and monetizing without compromising user experience.

1. Music recognition searching
application
Member A:Kwan Lok Hei Aaron (12213802)
Member B:XIE Siyu Shelley (12250643)
Member C:Cheung Lik Man(12206970)
Monday, April 22, 2013

2. WE WANT TO KNOW…..

5. Objectives
 Briefly introduce music recognition
 Compare the music recognition searching engine with
ordinary searching engine
 The Merits of music recognition searching
 The limitations of music recognition searching
 Find out what does the users really need for the music
searching engine

6. Music recognition searching application
 It is one of the applications using Speech recognition
technology.
 The application relies on:
 Fingerprinting music (spectrogram) technology.
 Speech-to-text technology.
 Operation:
1. Abundant of music’s fingerprints are stored in the database.
2. A user can tape the song for 10 seconds in order to get sufficient
information(fingerprint).
3. The app uploads the fingerprint to its corresponding service and do a
matching.
4. If the match is found, the app outputs the result to the user.

7. Application(1)
 Features:
 Biographies
 Other albums and tracks by that
artist
 Lyrics display
 Show the YouTube clips
 Show similar artists
 Tour dates
 Song’s album appearance
 Share via Email, Twitter, Facebook
or SMS

8. Application(2)
 Features:
 Artist biographies
 Tour dates
 A map of the location where
you tagged the song
 Show discography of the artist
Shazam
 Lyrics display
 Offer YouTube clips
 Recommended songs relating
to the one you tagged
 Share via Twitter and
Facebook

9. Video demonstration(Shazam1)
https://www.youtube.com/watch?feature=player_embed
ded&v=hny-G-0nUBM

10. Video demonstration(Shazam2)
https://www.youtube.com/watch?feature=player_embedded&v
=BJzCyaE6eKQ

11. Video demonstration(Soundhound)
https://www.youtube.com/watch?v=7c1
MnRaiRwg

12. Job Division
Data Process: PowerPoint Information
Creation: collection:
Member
A,B,C Member C Member A
Mind Map: Survey:
Web Search:
Member Member
Member B
A,B,C A,B,C
Question:11- Question:6-
Question:3-5
13 10
Member B
Member A Member C
Chart Chart Chart
Analysis Analysis Analysis
Creation Creation Creation

13. Information Collected
 Web Searching
 Searching tools: Google
 Keywords for searching:
 “voice search” technology
 Voice OR speech recognition principle
 Voice recognition –history
 Speech recognition *
 Voice recognition site: http://library.hkbu.edu.hk/main/index.html

14. Information Collected(2)
 Library Resources:
 Onesearch
 Keywords for searching:
 “Music recognition”
 Shazam OR Soundhound

15. Mind Map
http://www.mindmeister.com/251475311/voice-recognition

16. Online Survey
Aim:
To know what does the users really need for the
music searching engine
To know what is the advantages of music
recognition searching application over ordinary
searching engine
Survey Link:
https://qtrial.qualtrics.com/SE/?SID=SV_55XIo6w
FYrlinbL
No. of respond: 33

17. 3.How much do you like listening music?
Degree Nause Tireso Neutra Favorit Very Total
ous me l e like
Response
Answer 0 0 6 12 15 33

18. 4.What is your frequency of listening music in a
month?
Frequency Response %
Seldom 0 0%
1-2 time weekly 3 9%
2-5 times weekly 5 15%
5-9 times weekly 10 30%
Above 9 times 15 45%
weekly
Total 33 100%

19. 8
7
6
Frenquency and Devices
of Listening to Music
5
4 1-2 time weekly
2-5 times weekly
3
5-9 times weekly
2
Above 9 times
1 weekly
0
MP3
Cell phone
Computer
Other devices

20. 5.What do you often use to listen to music?
Device Response %
MP3 4 12%
Cell phone 23 70%
Computer 20 61%
Other devices 4 12%

21. Analysis to Question 3-5
 2 Factors that reduce music recognition
apps’ popularity:
1. Degree of Likeness
2. Advantages of Other Devices

22. Q6.What do you use when searching for a piece of music?
13%
4% 19%
A sentence of the lyrics
The name of a song
27% The singer
The melody
Asking to friends
37%

23. 10.What tools do you think that is the best way to search unknown music or
songs?(please arrange in order)
32
1
The worst way 0
0
0
1
19
A worse way 9 Other
0
4
0 Going to CD shop
11
Normal way 13
1 Asking friends
8
0
1 Internet
A better way 7
11
14 Music recognition applications
0 or software
1
The best way 4
21
7
0 5 10 15 20 25 30 35

24. Analysis(1)
 Most people always need to remember the detail of
the music or song such as the name, the lyrics and the
singer in order to find the music or song that they
desire to listen.
 They seldom use the melody to find the music or
song.
 Although most of the respondents chose Internet as
the best way for searching music or song, music
recognition application or software is the second
popular one.
 Music recognition application or software is getting
people’s awareness and support.

25. Q7.If an app can help you searching for music efficiently when you
don’t know much about the song, will you use it?
35
30
25
20
15 YES
10 NO
5
0
YES
NO

26. Q9.Do you think such apps can replace the music searching
website?(eg. google, yahoo, youtube)
Strongly Agree
Agree
Strongly Disagree
Disagree
Neither Agree nor Disagree Neither Agree nor Disagree
Agree
Strongly Agree
Disagree
Strongly Disagree
0 2 4 6 8 10 12 14

27. Analysis(2)
The demand and the popularity of music
recognition application or software is being
increase.
 People think this innovative recognition
technology may replace the traditional
searching methods.

28. Merits and Limitations

29. Chart and data in Question 11,12,13 (for
reference)
Are the users willing to help enlarge the database?
Yes
37%
No
63%

30. Are the users willing to help enlarge
the database?
Yes
37%
No
63%
OVER HALF (63%) of the respondents
refused to help enlarge the database

31. Limitation
Over half of the respondents refused to help
enlarge the database
As the enlargement of database relied heavily on
users’ contribution
 The database can not be enlarge
 thus, searching result may not be desirable

32. Why users love
Reasons of attractions
Large database (a big song storage)
3%
9% 15% Very convenient
9%
Free
13% 23%
Don't need to know much
information about the song
Results are comprehensive.(with
28% lyrics and youtube link)
Results are accurate
Other reason:

33. Why users love
 Reason of “Free” and “convenient” made up HALF (51%)
followed by “Large database”. Two options regarding “Results”
constituted only 9% each.
 “Free” and “convenient” are the main reasons of attraction followed
by “Large database”. On the other side, users don’t care much about
the results.
 The merits should be

34. Why users refuse to use
Reasons of why people refuse to use
4% 18%
35% Small database
Results are not accurate
27% Always sing out of pitch
No smartphone
6% Charge for US$5
10%
Other reason:

35. Why users refuse to use
Reason of “Charge for US$5” accounted for 35%
while “ inaccurate results” made up 27%, followed
by “Small database”(18%). “No smartphone
constituted the least ( 6%) while “always sing out of
pitch” had 10%.
What the users considered the most is the
CHARGE, followed by inaccurate results and small
database. And users are slightly concerned about if they
would sing out of pitch.

36. Merits and limitations
 The merits are mainly convenient and with large
database. Yet, some respondents said that they
wouldn’t help to enlarge the database. That’s the
conflicts
 And may have a vicious cycle:
 Database is not large enough and therefore the results will
not be very accurate, then less people to use, thus database
cannot be enlarged
 All users may leave because of the small database.
 Besides, users always consider about money. If the
app is charged for US$5, users may use GOOGLE
instead. It’s because there share the similar function
but music recognition is just more convenient.