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Outline. ADBOT Progress Report. Achievements Project Outputs Issues Risk Analysis Target for the next three months Project Manager: Aljon Rey P. Aniban Members: Emmanuel B. Cagadas Anna Mae C. Yap. Works that have been achieved over the past month. I. Achievements.

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Outline

Outline

ADBOT

Progress

Report

Achievements

Project Outputs

Issues

Risk Analysis

Target for the next three months

Project Manager:

Aljon Rey P. Aniban

Members:

Emmanuel B. Cagadas

Anna Mae C. Yap


I achievements

Works that have been achieved over the past month

I. Achievements


Achievements 1

Achievements (1)

  • Web Page Revision (2nd Semester):

    • Revision of Project Objectives

      • Utilization of the landmark-based audio fingerprinting algorithm which was based on Dan Ellis’s version of the algorithm used in Shazam’s music matching service.

      • Conversion of the current MatLab simulation of the algorithm to JAVA

    • Revision of Methodology and Framework

      • Segmentation of commercial audio template, extraction of prominent points, incorporating these points into pairs and efficient searching and matching of the stored commercials to the audio stream input.


Achievements 2

Achievements (2)

  • Project Web

    Page


Achievements 3

Achievements (3)

  • Matching of a single audio commercial to an audio of mixed contents

  • Matching of multiple commercial queries to an audio of mixed contents

  • Audio recording from microphone and audio playing in JAVA


Ii project outputs

progress milestones/deliverables achieved during the last month.

II. Project Outputs


Project outputs

Project Outputs

  • Revised Project Web Page

  • Matching of multiple commercial queries simulated in MatLab

  • Recording of audio commercials via microphone in JAVA

  • Partial gathering of additional audio commercial test data


Iii issues

III. Issues


Issues 1

Issues (1)

  • Integration of Octave and JAVA

    • For ease of use of the functions present in the MatLab simulation to JAVA by forming the same structure in Octave.

  • The need for boundary detection

    • To lessen the computation load and memory usage


Issues 2

Issues (2)

  • Large file size of wav files compared to other audio formats (i.e mp3)

  • Probable increase in computation time of the algorithm when Octave is incorporated with JAVA due to outside function calls.


Iv risk analysis

IV. Risk Analysis


Risk analysis

Risk Analysis

  • Real time versus Offline Commercial Detection

    • The time and space complexity that will be handled by the proposed system given that it is in real time.


V target for the next 3 months

V. Target for the next 3 months


Targets for the next 3 months

Targets for the Next 3 Months

  • Add boundary detection feature for queried commercials. (Currently being designed)

  • Generate the equivalent Octave codes from the simulated algorithm in MatLab

  • Incorporate generated Octave codes with the JAVA prototype of the application.


Targets for the next 3 months1

Targets for the Next 3 Months

  • Design the database prototype and data gathering of additional commercials.

  • Finalize the design of the whole application (GUI, database and underlying design of algorithm)

  • Test the efficiency of the modified algorithm.


End of presentation

Thank you

End of presentation.


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