Resources and papers on Audio, Music and Speech

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[http://cnx.org/content/col10338/latest/ Frequency and Music]
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[http://cnx.org/content/col10338/latest/ Frequency and Music]<br/>
An overview of frequency, harmonic (Fourier) series, and their
An overview of frequency, harmonic (Fourier) series, and their
relationship to music.
relationship to music.
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[http://cnx.org/content/col10250/latest/ Audio Localization]
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[http://cnx.org/content/col10250/latest/ Audio Localization]<br/>
This course has been created as an introduction to audio localization,
This course has been created as an introduction to audio localization,
and how beamforming can be applied in a real-time environment.
and how beamforming can be applied in a real-time environment.
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[http://cnx.org/content/col10303/latest/ Fundamentals of Digital Signal Processing Lab]
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[http://cnx.org/content/col10303/latest/ Fundamentals of Digital Signal Processing Lab]<br/>
The purpose of this lab is to familiarize students with the DSP
The purpose of this lab is to familiarize students with the DSP
development workstation in the signal processing lab by examining
development workstation in the signal processing lab by examining
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sampling frequency and its effects on aliasing.
sampling frequency and its effects on aliasing.
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[http://cnx.org/content/col10203/latest/ Intro to Digital Signal Processing]
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[http://cnx.org/content/col10203/latest/ Intro to Digital Signal Processing]<br/>
The course provides an introduction to the concepts of digital signal
The course provides an introduction to the concepts of digital signal
processing (DSP). Some of the main topics covered include DSP systems,
processing (DSP). Some of the main topics covered include DSP systems,
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wavelets, and filterbanks.
wavelets, and filterbanks.
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[http://cnx.org/content/col10252/latest/ Methods for Voice Conversion]
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[http://cnx.org/content/col10252/latest/ Methods for Voice Conversion]<br/>
This course explores methods in signal processing to perform voice
This course explores methods in signal processing to perform voice
conversion: producing the words from one speaker in the voice of
conversion: producing the words from one speaker in the voice of
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Hutchinson, Gina Upperman, and Brian VanOsdol.
Hutchinson, Gina Upperman, and Brian VanOsdol.
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[http://cnx.org/content/col10313/latest/ Musical Instrument Recognition]
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[http://cnx.org/content/col10313/latest/ Musical Instrument Recognition]<br/>
To detect the pitch and instrument of a monophonic signal. To
To detect the pitch and instrument of a monophonic signal. To
decompose polyphonic signals into their component pitches and
decompose polyphonic signals into their component pitches and
instruments by analyzing the waveform and spectra of each instrument.
instruments by analyzing the waveform and spectra of each instrument.
Elec 301 Project Fall 2005.
Elec 301 Project Fall 2005.
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[[Category:Developers stuff]]

Latest revision as of 12:30, 9 April 2010

Frequency and Music
An overview of frequency, harmonic (Fourier) series, and their relationship to music.

Audio Localization
This course has been created as an introduction to audio localization, and how beamforming can be applied in a real-time environment.

Fundamentals of Digital Signal Processing Lab
The purpose of this lab is to familiarize students with the DSP development workstation in the signal processing lab by examining sampling, analysis, and reconstruction of continuous-time signals. Specifically, we will first look at sampling/reconstruction of continuous-time signals. We will then examine time- and frequency-domain displays. Finally, we will examine the importance of sampling frequency and its effects on aliasing.

Intro to Digital Signal Processing
The course provides an introduction to the concepts of digital signal processing (DSP). Some of the main topics covered include DSP systems, image restoration, z-transform, FIR filters, adaptive filters, wavelets, and filterbanks.

Methods for Voice Conversion
This course explores methods in signal processing to perform voice conversion: producing the words from one speaker in the voice of another. This is the Elec 301 project of Justin Chen, Matthew Hutchinson, Gina Upperman, and Brian VanOsdol.

Musical Instrument Recognition
To detect the pitch and instrument of a monophonic signal. To decompose polyphonic signals into their component pitches and instruments by analyzing the waveform and spectra of each instrument. Elec 301 Project Fall 2005.

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