lnfzvvan
timer Asked: Apr 24th, 2020

Question Description

For this homework, you will be filtering noise from a sound recording. Assignment is broken into simple steps you can follow. Please follow instructions carefully and remember that you will only upload one workspace (*.mat) file. Make sure to name the clean_speech variable correctly.

  1. 1) Download the Matlab workspace from the link provided in Canvas. Move the downloaded file to the same folder as your script to make things simpler.
  2. 2) Load the downloaded workspace into Matlab.
    You can use the following command: load noisy_speech.mat
  3. 3) You will see two variables. fs = 16000Hz is the sampling frequency and noisy_speech is the vector which contains a recording of a spoken sentence with a very harsh noise.
  4. 4) You can use “soundsc” command to play the speech file: soundsc(noisy_speech,fs) NOTE: If you are working through USF AppGateway (Citrix), you can’t use soundsc command because it runs on USF servers, not your computer. You will either need a computer that runs a local copy of Matlab, or save the sound file, download it to your computer and play it there. See the following link to see how to save an audio file. You can use the *.vaw format. https://www.mathworks.com/help/matlab/ref/audiowri...
  5. 5) Determine what frequency band your desired signal is in, and what frequency band your noise occupy. You can do a frequency analysis (using FFT) to determine the noise frequency band. You will not be able to see your desired signal because noise will dominate it.NOTE: Feel free to use the internet for determining the frequency range of your desired signal (human speech).
  6. 6) Design a filter to filter out the noise using any method you would like, Matlab’s filterBuilder tool for example. Filter the noisy_speech signal to obtain a clean speech signal. Name this variable as clean_speech.
  7. 7) Do another frequency analysis (using FFT) to the filtered signal and compare it with the frequency domain of noisy signal. Verify that your desired signal is visible in the frequency domain plot.
  8. 8) Listen to your resulting sound file with soundsc(clean_speech,Fs). The speech signal should be clean without any harsh noise, something you wouldn’t mind hearing on a phone call. See the note under 4) if you are using Citrix.
page1image35452032 page1image35454528

9) When you are happy with the sound quality, save your workspace with: save lastname_firstname_hw4.mat

10) Upload your workspace file, which includes all the variables as well as your filter. 11) You won’t upload any .m files for this assignment.

Unformatted Attachment Preview

EEL 4102 - Spring 2020 - MATLAB Assignment 5 EEL4102 – Fall 2019 – Matlab Assignment 5 For this homework, you will be filtering noise from a sound recording. Assignment is broken into simple steps you can follow. Please follow instructions carefully and remember that you will only upload one workspace (*.mat) file. Make sure to name the clean_speech variable correctly. 1) Download the Matlab workspace from the link provided in Canvas. Move the downloaded file to the same folder as your script to make things simpler. 2) Load the downloaded workspace into Matlab. You can use the following command: load noisy_speech.mat 3) You will see two variables. fs = 16000Hz is the sampling frequency and noisy_speech is the vector which contains a recording of a spoken sentence with a very harsh noise. 4) You can use “soundsc” command to play the speech file: soundsc(noisy_speech,fs) NOTE: If you are working through USF AppGateway (Citrix), you can’t use soundsc command because it runs on USF servers, not your computer. You will either need a computer that runs a local copy of Matlab, or save the sound file, download it to your computer and play it there. See the following link to see how to save an audio file. You can use the *.vaw format. https://www.mathworks.com/help/matlab/ref/audiowrite.html 5) Determine what frequency band your desired signal is in, and what frequency band your noise occupy. You can do a frequency analysis (using FFT) to determine the noise frequency band. You will not be able to see your desired signal because noise will dominate it. NOTE: Feel free to use the internet for determining the frequency range of your desired signal (human speech). 6) Design a filter to filter out the noise using any method you would like, Matlab’s filterBuilder tool for example. Filter the noisy_speech signal to obtain a clean speech signal. Name this variable as clean_speech. 7) Do another frequency analysis (using FFT) to the filtered signal and compare it with the frequency domain of noisy signal. Verify that your desired signal is visible in the frequency domain plot. 8) Listen to your resulting sound file with soundsc(clean_speech,Fs). The speech signal should be clean without any harsh noise, something you wouldn’t mind hearing on a phone call. See the note under 4) if you are using Citrix. 9) When you are happy with the sound quality, save your workspace with: save lastname_firstname_hw4.mat 10) Upload your workspace file, which includes all the variables as well as your filter. 11) You won’t upload any .m files for this assignment.
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

This question has not been answered.

Create a free account to get help with this and any other question!

Similar Content

Related Tags

Brown University





1271 Tutors

California Institute of Technology




2131 Tutors

Carnegie Mellon University




982 Tutors

Columbia University





1256 Tutors

Dartmouth University





2113 Tutors

Emory University





2279 Tutors

Harvard University





599 Tutors

Massachusetts Institute of Technology



2319 Tutors

New York University





1645 Tutors

Notre Dam University





1911 Tutors

Oklahoma University





2122 Tutors

Pennsylvania State University





932 Tutors

Princeton University





1211 Tutors

Stanford University





983 Tutors

University of California





1282 Tutors

Oxford University





123 Tutors

Yale University





2325 Tutors