1. Music Matching
Speaker : 黃茂政
指導教授 : 陳嘉琳 博士

2. ? Introduction : Input Short piece of music Music Database Output
Candidate songs

3. Outline :
Introduction
Music Databases : Indexing Techniques and Implementation
Pattern Recognition
Conclusion

4. * music object : MIDI , WAV , other types of media
Introduction :
* music object : MIDI , WAV , other types of media
associated with music.
* requirements : unstructured search.
Input fault tolerance.
(duplication, elimination, disorder, irrelevant)
Saving of storage space and high performance.

5. MIDI vs. WAV format :
WAV file information : Channels, Sampling, Bits, Sound data

6. Music Databases : Indexing Techniques and Implementation
Arbee L. P. Chen
Chord-representation model.
Theme consists of a mdelody and a thythm.
* melody : sequence of the pitches of all notes.
* rhythm : sequence of the durations of all notes.
* chord : a signature of a melody.

7. Music Databases : Indexing Techniques and Implementation
Frequently-used chords
C : do, mi, sol
Dm : re, fa, la
Em : mi, sol, si
G : sol, si, re
Am : la, do, mi
Example :
measure with six notes : do, mi, mi, sol, sol, sol
“ C “ chord.

8. Music Databases : Indexing Techniques and Implementation
Using PAT-tree as Index Structure
Text : ababc
substring : ababc, babc, abc, bc, c ab b c
abc c
abc c
ababc
abc
babc bc c
Operation : Insert, Delete, Search.

9. Music Databases : Indexing Techniques and Implementation
Problem :
1. The chord-set decides the search performance.
2. When the users mistakenly rise the pitch to higher or
lower key, the search operation will repeal.
“We must alter the representation model to solve this problem.”

10. Pattern Recognition : MIDI curve feature A/D shift Candidate songs
(sampling)
Critical
value
shift
Normalized
crosscorrelation
Candidate songs

11. Sampling :
精確 與 效率 trade off

12. Index l is the shift parameter.
Normalized crosscorrelation :
x : The (input) pattern.
y : The reference pattern or template for a particular class.
r : The extent of x over which the match occurs.
Index l is the shift parameter.

13. Normalized crosscorrelation :
<example>

14. chord-representation
Conclusion :
chord-representation
pattern recognition
unstructured search v x
fault tolerance * v
storage space v v
performance ? ? /
Acknowledge : 蘇文鈺 老師