Get Instant Help From 5000+ Experts For

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

Editing:Proofread your work by experts and improve grade at Lowest cost

And Improve Your Grades
Phone no. Missing!

Enter phone no. to receive critical updates and urgent messages !

Attach file

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Guaranteed Higher Grade!
Free Quote
Developing and Evaluating Speech Signal Analysis Plugins

Assessment Task Details and Instructions

Develop and evaluate a suite of speech signal analysis plugins. These plugins should give the features or characteristics of speech segments in the time and frequency domains. The suite should give at least two time-domain features (e.g. RMS values, peak, ZCR, etc.) More features (up to 4) may help achieve higher marks. In the frequency domain, the suite should give a straightforward FFT spectrum and a power spectrum density estimation using the Welch method. In coding and testing the algorithms, you should start with a speech segment sampled at the most common CD sampling rate of 44.1 kHz and then down sample it to 16 kHz or 8 KHz of your choice. All subsequent processing should be done with the down sampled speech signals. There is no requirement of developing specific graphic user interfaces (GUIs) for the plugins, but graphic presentations produced using Matlab should be used to clearly illustrate your results where applicable, and these illustrations should be included in the AES conference paper type of written work.

Please refer to the assessment criteria attached separately for a breakdown of grades.

A written submission in the form of a short conference paper (2000-4000) should be produced to accompany your Matlab codes. The Matlab codes should include detailed comments and be added to the end of the main body of the conference paper.

This submission should include appropriately labelled graphs of your plugin performance (e.g., frequency and time domain plots). In the written submission please include:

  • An abstract section
  • An introduction section which will supply theoretical overview selection of the methods you used for speech signal analysis, and why you chose these methods (including appropriate references)
  • A method section describing your implementation
  • A results section demonstrating the performance of your implementation (this is a good place for plots), and discussion/evaluating your implementation
  • A conclusion section which will summarise all of the above, and if appropriate, make suggestions for further work
  • A references section, appropriately formatted as per an AES conference paper

sales chat
sales chat