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Localized Key-Finding: Algorithms and Applications. Ilya Shmulevich, Olli Yli-Harja Tampere University of Technology Tampere, Finland October 4, 1999. Outline. Review of key-finding algorithms Median-based filters Graph-based smoothing of class data

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Localized Key-Finding: Algorithms and Applications

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## Localized Key-Finding: Algorithms and Applications

Ilya Shmulevich, Olli Yli-Harja

Tampere University of Technology

Tampere, Finland

October 4, 1999

### Outline

• Review of key-finding algorithms

• Median-based filters

• Graph-based smoothing of class data

• Application of algorithm to music pattern recognition

### Key-Finding Algorithm

Most stable pitch classes should occur most often.

• probe tone profile – set of 12 probe tone ratings for a given key

• 24 profiles (12 major and 12 minor)

• Input to algorithm is a 12 element vector d with elements of total duration of the 12 tones in the examined music.

• Correlate vector dwith 24 profile vectors and produce 24 element vector of correlationsr. The highest correlation is the key.

• Slide window across sequence of notes and run algorithm. The vector of results is t.

rmax

d

t

### Median-Based Filters

• A filter window with length k scans through a set of elements and sorts them.

• The middle value is selected as the filter value.

• The window moves one element to the right and repeats the steps.

• Recursive median filters replace some of the input elements with previously selected output elements.

Disadvantage:

Class data cannot be ordered.

### Graph-Based Smoothing

Relax requirements of metric space to allow for “distance” between elements of class data.

“Distance” – Based on similarity between two keys.

High similarity corresponds to small distance.

• Testing was done using this method. The output of the algorithm was almost identical to the results from analysis done by ‘experts’.

### Application to MPR

Used methods discussed to correct pitch error

Types of Pitch Error:

Objective

Perceptual

Less stable elements are poorly remembered. To compute perceptual pitch error, must have knowledge of the key. The localized key-finding algorithm may be used to obtain this.