[AUDITORY] MaxAlea: A Comprehensive Stochastic Toolkit for Max ("cf@xxxxxxxx" )

Subject: [AUDITORY] MaxAlea: A Comprehensive Stochastic Toolkit for Max From: "cf@xxxxxxxx" <cf@xxxxxxxx> Date: Tue, 23 Jul 2024 16:40:21 +0000 --_000_AS1P195MB1541A7E7B44126A239DAFDDFAAA92AS1P195MB1541EURP_ Content-Type: text/plain; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable Hi all, I=92ve just finished porting MaxAlea over to the new decade. I made a Max p= ackage to facilitate the installation process. I think this will be of inte= rest to many Max users in research and creation. This version only works on= MacOS, but I=92ve included the sources if someone with a Windows environme= nt would like to compile it for PC. Info and links to the package below. Regards, Carl MaxAlea: A Comprehensive Stochastic Toolkit for Max MaxAlea is a newly modernized collection of over 30 objects for Max, design= ed to facilitate the use of stochastic processes in audio, music, and multi= media applications. Originally developed in 1996 and recently updated using= C++ and the MIN API, MaxAlea offers a robust set of tools for incorporatin= g probabilistic elements into Max patches. Key Features: - Diverse random distributions (e.g., Gaussian, Poisson, Weibull) - Markov chain objects for first and second-order transitions - Random walk and 1/f noise algorithms - Data mapping and scaling utilities - Real-time manipulation of stochastic processes Potential Applications for Auditory Research and MIR: 1. Modeling Auditory Perception: - Use probability distributions to simulate variability in auditory resp= onses - Apply Markov chains to model transitional probabilities in speech or m= usic perception 2. Music Information Retrieval: - Implement stochastic models for genre classification or style analysis - Utilize random walk algorithms for exploring tonal spaces or chord pro= gressions 3. Generative Audio and Music: - Create probabilistic models for algorithmic composition - Generate synthetic datasets for training and testing MIR algorithms 4. Psychoacoustic Experiments: - Design controlled random stimuli for perceptual studies - Implement adaptive procedures with stochastic elements 5. Sound Synthesis and Processing: - Apply controlled randomness to synthesis parameters for natural-soundi= ng results - Use 1/f noise for creating realistic environmental soundscapes 6. Analysis of Musical Structure: - Employ Markov models to analyze and generate musical sequences - Study statistical properties of various musical styles MaxAlea provides researchers and practitioners in auditory perception and m= usic information retrieval with a flexible, real-time environment for imple= menting and exploring stochastic models. Its integration with Max allows fo= r easy combination with other audio processing and analysis tools, making i= t valuable for both experimental design and creative applications. For more information and access to the toolkit, visit: https://github.com/c= arlfaia/MaxAlea --_000_AS1P195MB1541A7E7B44126A239DAFDDFAAA92AS1P195MB1541EURP_ Content-Type: text/html; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable <html xmlns:v=3D"urn:schemas-microsoft-com:vml" xmlns:o=3D"urn:schemas-micr= osoft-com:office:office" xmlns:w=3D"urn:schemas-microsoft-com:office:word" = xmlns:m=3D"http://schemas.microsoft.com/office/2004/12/omml" xmlns=3D"http:= //www.w3.org/TR/REC-html40"> <head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3DWindows-1= 252"> <meta name=3D"Generator" content=3D"Microsoft Word 15 (filtered medium)"> <style></style> </head> <body lang=3D"en-FR" link=3D"#467886" vlink=3D"#96607D" style=3D"word-wrap:= break-word"> <div class=3D"WordSection1"> Hi a= ll,<o:p></o:p> &nbs= p;<o:p></o:p> I=92= ve just finished porting MaxAlea over to the new decade. I made a Max packa= ge to facilitate the installation process. I think this will be of interest= to many Max users in research and creation. This version only works on MacOS, but I=92ve included the sources if someo= ne with a Windows environment would like to compile it for PC.<o:p></o:p> &nbs= p;<o:p></o:p> Info= and links to the package below.<o:= p></o:p>  <o:p></o:p></= span> Rega= rds,<o:p></o:p> &nbs= p;<o:p></o:p> Carl= <o:p></o:p> &nbs= p;<o:p></o:p>  <o:p></o:p></= span>  <o:p></o:p></= span> MaxAlea: A Comprehe= nsive Stochastic Toolkit for Max<o:p></o:p>  <o:p></o:p></= span> MaxAlea is a newly = modernized collection of over 30 objects for Max, designed to facilitate th= e use of stochastic processes in audio, music, and multimedia applications.= Originally developed in 1996 and recently updated using C++ and the MIN API, MaxAlea offers a robust set of tools fo= r incorporating probabilistic elements into Max patches.<o:p></o:p><= /p>  <o:p></o:p></= span> Key Features:<o:p><= /o:p> - Diverse random di= stributions (e.g., Gaussian, Poisson, Weibull)<o:p></o:p> - Markov chain obje= cts for first and second-order transitions<o:p></o:p> - Random walk and 1= /f noise algorithms<o:p></o:p> - Data mapping and = scaling utilities<o:p></o:p> - Real-time manipul= ation of stochastic processes<o:p></o:p>  <o:p></o:p></= span> Potential Applicati= ons for Auditory Research and MIR:<o:p></o:p>  <o:p></o:p></= span> 1. Modeling Auditor= y Perception:<o:p></o:p>    - Use = probability distributions to simulate variability in auditory responses<o:p= ></o:p>    - Appl= y Markov chains to model transitional probabilities in speech or music perc= eption<o:p></o:p>  <o:p></o:p></= span> 2. Music Informatio= n Retrieval:<o:p></o:p>    - Impl= ement stochastic models for genre classification or style analysis<o:p></o:= p>    - Util= ize random walk algorithms for exploring tonal spaces or chord progressions= <o:p></o:p>  <o:p></o:p></= span> 3. Generative Audio= and Music:<o:p></o:p>    - Crea= te probabilistic models for algorithmic composition<o:p></o:p>    - Gene= rate synthetic datasets for training and testing MIR algorithms<o:p></o:p><= /span>  <o:p></o:p></= span> 4. Psychoacoustic E= xperiments:<o:p></o:p>    - Desi= gn controlled random stimuli for perceptual studies<o:p></o:p>    - Impl= ement adaptive procedures with stochastic elements<o:p></o:p>  <o:p></o:p></= span> 5. Sound Synthesis = and Processing:<o:p></o:p>    - Appl= y controlled randomness to synthesis parameters for natural-sounding result= s<o:p></o:p>    - Use = 1/f noise for creating realistic environmental soundscapes<o:p></o:p></span= >  <o:p></o:p></= span> 6. Analysis of Musi= cal Structure:<o:p></o:p>    - Empl= oy Markov models to analyze and generate musical sequences<o:p></o:p></span= >    - Stud= y statistical properties of various musical styles<o:p></o:p>  <o:p></o:p></= span> MaxAlea provides re= searchers and practitioners in auditory perception and music information re= trieval with a flexible, real-time environment for implementing and explori= ng stochastic models. Its integration with Max allows for easy combination with other audio processing and analy= sis tools, making it valuable for both experimental design and creative app= lications.<o:p></o:p>  <o:p></o:p></= span> For more informatio= n and access to the toolkit, visit: <a href=3D"https://github.com/c= arlfaia/MaxAlea">https://github.com/carlfaia/MaxAlea</a><o:p></o:p></sp= an>  <o:p></o:p></= span> <o:p> </o:p></= span> </div> </body> </html> --_000_AS1P195MB1541A7E7B44126A239DAFDDFAAA92AS1P195MB1541EURP_--

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DAn Ellis <dpwe@ee.columbia.edu>
Electrical Engineering Dept., Columbia University