gt;
> Sent:"A discussion list for music-related DSP"
>
>
> Date:Sat, July 12, 2014 6:39 pm
>
> Subject:Re: [music-dsp] Frequency based analysis alternatives ?
>
> >
>
> > Adaptive models with frames or overcomplete representations might
> be
>
>
ot;
Sent:"A discussion list for music-related DSP"
Date:Sat, July 12, 2014 6:39 pm
Subject:Re: [music-dsp] Frequency based analysis alternatives ?
>
> Adaptive models with frames or overcomplete representations might
be
> interesting. Then you can decompose the signal wit
Adaptive models with frames or overcomplete representations might be
interesting. Then you can decompose the signal with a broader class of basis
functions, such as symmetrically windowed sinusoids, chirps, exponentially
decaying sinusoids and whatever. The point is to have a sparse representat
.
From:"Olli Niemitalo"
Sent:"A discussion list for music-related DSP"
Date:Thu, July 10, 2014 6:08 pm
Subject:Re: [music-dsp] Frequency based analysis alternatives?
> There are chirp(let) transforms that represent the signal
There are chirp(let) transforms that represent the signal as a sum of
Gaussian-enveloped bursts of (typically) linearly time-varying
frequency. They work better than windowed short-time Fourier
transforms for signals that are non-stationary. See for example:
http://www.eurasip.org/Proceedings/Eusip
12:05 pm
Subject:Re: [music-dsp] Frequency based analysis alternatives?
> STransform, see e.g. http://djj.ee.ntu.edu.tw/S_Transform.pdf
> --
> dupswapdrop -- the music-dsp mailing list and website:
> subscription info, FAQ, source code archive, list archive, book
reviews,
> dsp
STransform, see e.g. http://djj.ee.ntu.edu.tw/S_Transform.pdf
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dupswapdrop -- the music-dsp mailing list and website:
subscription info, FAQ, source code archive, list archive, book reviews, dsp
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http://music.columbia.edu/cmc/music-dsp
http://music.columbia.edu/mailman/listinfo/music-dsp
?
From:"Jamie Bullock"
Sent:"A discussion list for music-related DSP"
Cc:"music-dsp@music.columbia.edu"
Date:Thu, July 10, 2014 12:37 am
Subject:Re: [music-dsp] Frequency based analysis alternatives?
>
> There is Antoine Schmitt&#x
There is Antoine Schmitt's Wavelet-based method, implementation available under
an MIT license:
https://github.com/antoineschmitt/dywapitchtrack
It is optimized for voice, but I have found it generally works well with PNP
sounds.
Jamie
> On Jul 9, 2014, at 1:03 PM, "Rohit Agarwal" wrote:
>
ly 10, 2014 12:11 am
Subject:Re: [music-dsp] Frequency based analysis alternatives?
> Gabor transform or Wigner Distribution analysis
> or their combination may be used.
>
> See the following tutorial paper on joint-domain time-frequency
analysis:
>
> "Wigner Distribution R
Were your wavelets symmetric/asymmetric? What kind of basis functions
did you work with?
From:j...@cs.bath.ac.uk
Sent:"A discussion list for music-related DSP"
Date:Wed, July 9, 2014 10:59 pm
Subject:Re: [music-dsp] Frequ
Gabor transform or Wigner Distribution analysis
or their combination may be used.
See the following tutorial paper on joint-domain time-frequency analysis:
"Wigner Distribution Representation and Analysis of Audio Signals: An
Illustrated Tutorial Review"
Douglas Preis and Voula Chris Georgopoulos
We use wavelets in a pitch-tracking application some years ago
(John ffitch and Wafaa Shabana, A Wavelet-based Pitch Detector for
Musical Signals; Proceedings of DAFx99, 101--104). We did try some
other wavelet attempts with nothing useful.
==John ff
Quoting Rohit Agarwal :
Most of our mo
>What are the alternatives to the FFT? Have wavelets been
>used for real world solutions?
Sure, wavelets get used. Maybe more in image/video than audio, but I'm
certain someone can come up with some examples of wavelet audio
applications.
>If an app needs much higher time resolution
>and there ar
Most of our modern DSP techniques that we use for the analysis of sound
signals are based on the FFT as a first step. This imposes limits on time
resolution since the FFT window has to be wide. For most natural sound
apps this is no hindrance as the rate of events is commonly slow. Speech
recogn
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