Connexions

You are here: Home » Content » The detecting process of FFT matrix approach
Content Actions
Lenses

What is a lens?

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

This content is ...
Affiliated with (?)
This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • This module is included inLens: Rice University ELEC 301 Project Lens
    By: Rice University ELEC 301As a part of collection:"ELEC 301 Projects Fall 2006"

    Click the "Rice University ELEC 301 Projects" link to see all content affiliated with them.

    Rice University ELEC 301 Projects
  • This module is included inLens: Rice University OpenCourseWare
    By: OpenCourseWare ConsortiumAs a part of collection:"ELEC 301 Projects Fall 2006"

    Click the "Rice University OCW" link to see all content affiliated with them.

    Rice University OCW
Tags

(?)

These tags come from the endorsement, affiliation, and other lenses that include this content.

The detecting process of FFT matrix approach

Module by: Yiming Wang

Summary: Describe the detailed information about the detecing process of the FFT matrix approach.

The Detecting Process:

So we load the song we want to detect into Matlab. The use would just type Genre (‘song’). After that, our program would do the same process of windowing; it did to the songs in the database (FFT of windows of 15ms length). This will leave us with another, smaller matrix that represents the song we want to test. We basically perform an operation of dot production for each column of the tested song with our data base. ( The operation of Dot Product gives a bigger value for a vector that is similar, and a small value for one that is different ). So we basically check for the max. value of each dot product operation. And this means that this column (frequencies) of the tested song is really close to this column that represent a certain genre. We then ask Matlab about the genre this column represented. And save this value. After doing this for all the columns of the tested song, we’ll end up with a bunch of numbers going from (1-5). Finally we check which number is the most frequent in the group, and this will tell us what genre the tested song is most likely to be.

Comments, questions, feedback, criticisms?

Send feedback