Projects
1st Project : Linear Prediction
During this project you will explore the Linear Prediction theory and an implementation in Python of a Linear Prediction based Analysis and Synthesis system for speech. In the Python code there are some incomplete command lines that are waiting for you to fill them in. Once you do this, you can play with the code to do various speech modifications in an input speech signal. In this project you will use the code in the Python file: lpc_as_toyou.py. You will play with a speech signal in a WAV format (speechsample.wav). Submit your project via e-mail to sisamaki@csd.uoc.gr.
More Helpful files: Python script, .wav file, More files (Right Click -> Save as ...)2nd Project : Sinusoidal Modeling
During this project you will explore the Sinusoidal Representation of speech signals and you will
work with an implementation in Python of the Sinusoidal Model (SM) suggested by McAulay and
Quatieri. In the provided Python code, there are some empty command lines that are waiting for
you to fill in. Once you do this, you can play with the code to perform speech analysis and synthesis
based on SM.
In this project you will use the code in the Python file: SinM_test_hy578.py. You will play with
a speech signal in a wav format named arctic_bdl1_snd_norm.wav. Submit your project via e-mail to sisamaki@csd.uoc.gr.
3rd Project : Vector Quantization & LPC coding
During this project you will explore the quantization process. More specifically you will develop a uniform scalar quantizer and a vector quantizer. You will apply this into the Linear Prediction algorithm studied during the 1st project. Submit your project via e-mail to sisamaki@csd.uoc.gr.
More Helpful files: Dataset (Right Click -> Save as ...)4th Project : Speaker Identification
During this project you will develop an automatic speaker identification system. More specifically the identification system is split into two modules; the features extraction module and the classification or machine learning module which you will develop. You will use MFCCs as features and GMMs as classification module. Submit your project via e-mail to sisamaki@csd.uoc.gr.
More Helpful files: Dataset, Tutorial