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Factors Affecting Music Retrieval in Query-by-Melody Christian Godi PowerPoint PPT Presentation

Factors Affecting Music Retrieval in Query-by-Melody Christian Godi FACTORS Accuracy of the Query Provider Query transcription Accuracy of the acoustic Front End Query Length What is Query-by-Melody? Query Transcription? Length of a Query? Architecture of QBM System Query Query

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Factors Affecting Music Retrieval in Query-by-Melody Christian Godi

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Factors affecting music retrieval in query by melody christian godi l.jpg

Factors Affecting Music Retrieval in Query-by-MelodyChristian Godi


Factors l.jpg

FACTORS

  • Accuracy of the Query Provider

  • Query transcription Accuracy of the acoustic

    Front End

  • Query Length


What is l.jpg

What is

  • Query-by-Melody?

  • Query Transcription?

  • Length of a Query?


Architecture of qbm system l.jpg

Architecture of QBM System

Query

Query

Ordered List

Front-End

Back End

Song ID’s

(Signal)

(transcription)

Melody

Database


Systems databases l.jpg

SYSTEMS & DATABASES

  • Cuby Hum Back End

    It performs an approximate match between a relatively short query transcription

    and a much longer monophonic melody. This match is based on a Dynamic Programming procedure which computes Melody Distance.

  • Acoustic Front Ends

    1. Solo Explorer

    2. Ear Analyzer

    3. MAMI

  • The Databases

    1. Query Database

    2. Melody Database


Errors l.jpg

Errors

  • The Cuby Hum engine distinguishes

    between the following errors

    1. Interval Change

    2. Interval Transposition

    3. Interval Insertion or Deletion

    4. Note Insertion

    5. Note Deletion

    6. Duration Error


Evaluation methodology l.jpg

Evaluation Methodology

  • Indicator of Query Transcription Accuracy

    Indicator of QTA is based on comparison of automatically generated and manually verified transcriptions of all the queries in a query database.

    Total Transcription Error (TTE)

    TTE = no. of deletions + insertions + substitutions

No. of notes in manual transcriptions


Slide8 l.jpg

Indicator of Music Retrieval Accuracy

The QBM system is supposed to produce an output list of melodies and a target is said to be retrieved correctly if at least one of its

characterizing melodies appear in that list.

The indicator of music retrieval accuracy that is independent of any output list is the MEAN RECIPROCAL RANK (MRR).

MRR = 1/NqΣ1/ranki

Nq= the number of tested queries

Ranki = the position of the melody of the target of query I in an

output list of size Sl = Sd


Slide9 l.jpg

Under the assumption that each target is characterized by one melody, the mean uncertainty about finding target Ti(i=1,….,Sd) in the output list L[q(Ti)] generated for some query q(Ti) of that target, can be computed as

H(Ti εL[q(Ti)]) = -E[logP(Ti εL[q(Ti)]) ]

RIF = log P = log P

log Po log Sl/Sd

RIF = Remaining information Factor

The QBM system that is capable of always putting the target melody

on top of the output list will yields a RIF=0 whereas a QBM system that behaves like that random system will yield a RIF =1.


Impacts l.jpg

IMPACTS

  • IMPACT OF USER PERFORMANCE

    Backend when supplied with the perfect query transcriptions it

    behaves like a perfect system with RIF=0. But when supplied with

    real life queries the performance degrades significantly.

  • IMPACT OF THE FRONT END TRANSCRIPTION ACCURACY

    Front ends with the highest transcription accuracies yield the

    highest music retrieval accuracies.


Slide11 l.jpg

RIF

0,3

  • IMPACT OF THE QUERY LENGTH

0,25

0,2

0,15

0,1

0,05

L min

10

15

20

25

30

35

40

45

RIF as a function of minimal query length (no. of notes)

By plotting the retrieval performances using RIF for the different

front-end/backend combinations as a function of minimal query length one Can see that the performance differences caused by changes of the Front end remain equally important irrespective of this length., RIF starts to raise as soon as query counts <20 notes


Conclusion l.jpg

Conclusion

  • The first conclusion of this study is that the

    RIF is a robust and attractive indicator of

    the music retrieval accuracy of a QBM

    system.

  • The second Conclusion is that due to the limited accuracy of the query provider, the music retrieval accuracy of QBM system, does not yet approach the perfect accuracy RIF=0 one could have hoped for.


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