Speed of Sound (video) | Waves and sound | Khan Academy

Science AP®︎ Physics 1 Waves and sound Introduction to sound

Sound Properties: Amplitude, period, frequency, wavelength (video) | Khan Academy

Science AP®︎ Physics 1 Waves and sound Introduction to sound

San Francisco State University, School of Engineering: Faculty / Staff: Profiles and Office Hours Faculty: Todor Cooklev

T. Cooklev has published over 20 journal papers and over 30 conference papers in the areas of digital signal processing, audio and video compression, fast algorithms, and wireless communications. For one of his papers he received the Best Paper Award at the 1994 IEEE Asia-Pacific Conference on Circuits and Systems, Taipei, Taiwan. He is the inventor on 5 issued and about 12 pending patents in the United States.

San Francisco State University, School of Engineering: Faculty / Staff: Profiles and Office Hours Faculty: Tom Holton

Tom Holton, Ph.D.Tom Holton Electrical/Computer Engineering Program Head &Professor of Electrical EngineeringDiscipline: DigitalOffice: SCI 170Office Hours: Click herePhone: (415) 338-1529Fax: (415) 338-0525Email: tholton@sfsu.edu

java – Split audio file (mp3, wav, wma) into 1s chunks – Stack Overflow

I know this doesn’t address your problem directly but typical technique is to divide into 2^n samples chunks and process; possibly with overlapping blocks, possibly applying a window function (Google it) depending on desired frequency response. If you are modifying the FFT and applying an inverse you will want overlapping blocks, cross-faded in output, because you will get audible clicks between blocks if the apparent phase (or the 0Hz constant term) changes. BTW, frequency (Hz) is index * sample_rate / block_size

Coursera Audio Signal Processing for Music Applications

Video LecturesHelp CenterHaving trouble viewing lectures? Try changing players. Your current player format is html5. Change to flash. Week 1 – Introduction

via Coursera.

9. Signals and Sampling Theory

8 Spectrogram

Often there are times when you may want to examine how the power spectrum of a signal (in other words its frequency content) \emph{changes} over time. In speech acoustics for example, at certain frequencies, bands of energy called formants may be identified, and are associated with certain speech sounds like vowels and vowel transitions. It is thought that the neural systems for human speech recognition are tuned for identification of these formants.

http://gribblelab.org/scicomp/09_Signals_and_sampling.html

PHYS 250 uploaded a video 1 year ago

23:11

SC01 : Scipy Root Finding

by PHYS 250

1 year ago459 views

First screen cast! Select 720p (HD) for full screen viewing. This screen cast contains an introduction to loading modules in Python as applied to scipy.optimize. We also learn to u

▶ SC09 : FFT – YouTube

Published on Apr 15, 2014

FFT in python. We focus on a basic signal processing analysis to show many of the details in performing ffts.

▶ Music Information Retrieval using Scikit-learn (MIR algorithms in Python) – Steve Tjoa – YouTube

Music Information Retrieval using Scikit-learn (MIR algorithms in Python) – Steve Tjoa

Frequency Analysis of audio file with Python- Numpy/Scipy – haskell102

Frequency Analysis of audio file with Python- Numpy/Scipy

python – How to get audio spectrum analysis? – Programmers Stack Exchange

Here’s the numpy module which came up second in my search. So it looks like you shouldn’t need to do much coding at all.

python – Spectrogram of wav file – Signal Processing Stack Exchange

I am calculating spectrogram of a audio file of 36 second using the following code snippet:

Frequency Analysis in Python -Print letters with frequency rather than numbers with frequency – codedisqus.com

This will also return the (char, frequency) tuple in descending order of frequency.