Skip to content Skip to navigation

OpenStax-CNX

You are here: Home » Content » Match Recognition System

Navigation

Lenses

What is a lens?

Definition of a lens

Lenses

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

What is in a lens?

Lens makers point to 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 member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

This content is ...

Affiliated with (What does "Affiliated with" mean?)

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.
  • Rice University ELEC 301 Projects

    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 Digital Scholarship

    This module is included in aLens by: Digital Scholarship at Rice UniversityAs a part of collection: "ELEC 301 Projects Fall 2006"

    Click the "Rice Digital Scholarship" link to see all content affiliated with them.

Also in these lenses

  • Lens for Engineering

    This module is included inLens: Lens for Engineering
    By: Sidney BurrusAs a part of collection: "ELEC 301 Projects Fall 2006"

    Click the "Lens for Engineering" link to see all content selected in this lens.

Recently Viewed

This feature requires Javascript to be enabled.
 

Match Recognition System

Module by: Andre Mosley, Yu-Heng Lee, John Broadway, Po T Wang. E-mail the authors

Summary: This module explains how we implemented the matched filter phase of our audio recognition system.

To implement the Match Recognition System for our program, we used a basic matched filter that compares the input song’s fingerprint to each fingerprint in the database. Because we are using compact representations for each song, the matched filter will not take an insane amount of time to complete. In order to improve the speed of the algorithm even more, we decided to implement the filter in the frequency domain since it is involves simple matrix multiplication.

First of all, the input song goes through the Audio Fingerprint Generator so that we have its compact representation. Next, our system normalizes this representation, takes its FFT, and compares it to the normalized FFT of each of the fingerprints in the database. At this point the fingerprints are all in the frequency domain, so the only thing left to do to implement the matched filter is to multiply the input song’s representation with each one of the database representations. This process requires zero-padding the shorter signal in the comparison so that the two matrices are the same dimensions before actual multiplication. The max(max()) function in Matlab takes the maximum value in the matrix, which corresponds to the matched filter “spike”. The database signal that returns the largest spike when compared to the input signal is our most probable match and the database index of this matched song is used to index the name of that corresponding song from the array that holds the names of all database songs. Our system also does this process for the second highest match. The output of the Match Recognition System is just the two most probable match titles, and their corresponding spike values. This allows users to see the confidence level for each match.

Figure 1
Figure 1 (Graphic1.png)

Content actions

Download module as:

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

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

What is in a lens?

Lens makers point to 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 member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks