Concept

Audio editing software

Related notebooks (7)

Block Processing of Audio Files Using Stateful FIR Filters

Block-processing of audio files[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

This notebook shows a simple way to process audio files (in WAV format) in a block-by-block fashion; this is useful in two cases 1. when you want to process a data stream in real time but you can accept a small processing delay; in this case a buffered approach can yield computational gains 2. when you need to process a large file that does not fit entirely into

Investigating the Effect of Phase on Sound Perception

Hearing the phase of a sound[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will investigate the effect of phase on the perceptual quality of a sound. It is often said that the human ear is commercial-grade audio equipment takes place in the magnitude domain only. In [1]: %matplotlib inline import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython from scipy.io import wavfile In [2]: plt.rcParams["figure.fig

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will explore various ways to implement a system that changes the voice of a speaker. Typical applications for these techniques, strictly sorted by plausibility, include international spy missions and prank telephone calls, and devices such as the one displayed here can be easily bought on the web... or in a novelty shop. No description has been provided for t

Filtering Music: Extracting Audio Frequencies Using Filters

Filtering Music[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will design and use filters to extract specific audio frequencies from a music file. In [1]: %matplotlib inline import matplotlib.pyplot as plt import numpy as np import IPython import scipy.signal as sp from scipy.io import wavfile infringment...) In [2]: IPython.display.Audio(s, rate=SF) Out[2]: Your browser does not support the audio element.

Extracting the bas

Fairness Week 1: University Admissions – Solutions

Fairness Week 1: University admissions¶{.anchor-link} {#Fairness-Week-1:-University-admissions}

How to use this notebook Simply read the text and follow the instructions.
This notebook contains code cells, which can be modified and must be executed to see the result of their content.
To execute a cell, select it and click on the play button (▶) in the tool bar, or type Shift + Enter or Ctr + Enter. As the variables contained in a cell are stor

Implementing a Fractional Resampler using Local Lagrange Interpolation

FIR Resampling[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will implement a simple fractional resampler that uses local Lagrange interpolation. The resampler can be used to perform any rational sampling rate change (but beware of aliasing when downsampling!) In [1]: import numpy as np import IPython from scipy.io import wavfile Local Lagrange interpolation[4]¶ To perform resampling we will need to compute subsample values and, in

Advantages of Digital Transmission over Analog Transmission

[1]Paolo Prandoni, [2]EPFL Analog vs Digital Transmission In this notebook we will explore the advantages of digital transmission over analog transmission. We will model the case of transmission over a long (e.g. transoceanic) cable in which several repeaters are used to compensate for the attenuation incurred by the signal. In [1]: import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython from scipy.io import wavfile plt.rcParams["figure.figsize"] = (14,4)

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.