11 votes
Accepted

What's the correct graphical interpretation of a series of MFCC vectors?

The way MFCC's are always used is by feeding them into the classifier. This can be done on a frame-by-frame basis (12x1 vector), or by concatenating (...
jojeck's user avatar
  • 11.1k
6 votes
Accepted

Palm Pilot Graffiti

If you are looking for a good explanation of some of the methods used in projects like GRAIL look here: Back to the Future of Hand Writing Recognition
FallenNode's user avatar
6 votes
Accepted

Understanding GCC-PHAT as a Feature

Let there be two microphones, $x_1(t), x_2(t)$ capturing a source, $s(t)$, with some additive noise $n_{1,2}(t)$ that is uncorrelated with the source and with each other (i.e., its effect can be ...
orchi_d's user avatar
  • 577
6 votes
Accepted

Resource recommendations to learn audio processing

Here are a few books that might be helpful: The Scientist and Engineer's Guide to Digital Signal Processing A good resource for you to get familiarized with DSP in general. Understanding Digital ...
Ahsan Yousaf's user avatar
  • 1,533
5 votes

Accurate phase calculation in sinusoidal linear regression?

What other "modern" methods exist for accurate phase extraction? Unless the frequencies in the signal are phase locked to your sampling clock an FFT is not a great way to determine either ...
Hilmar's user avatar
  • 44.7k
4 votes

ORB Algorithm: What Is Intensity Centroid?

Because wo want to get the centroid of the image(a block/patch) by the intensity. m00:p = q = 0,sum the intensity matrix. m10:p =1,q = 0,sum of the x-direction. m01:p = 0,q = 1,sum of the y-direction. ...
LingJun's user avatar
  • 41
4 votes

Why do we need multiple layers in each octave and multiple octaves in SIFT?

In music theory, an octave is an interval in frequency, from a frequency $f$ to frequency $2f$. For example "an octave higher" means "twice the frequency". Expressed as wavelength ...
Olli Niemitalo's user avatar
4 votes

Resource recommendations to learn audio processing

Julius O. Smith's original book is here: Julius O. Smith III,'s Spectral Audio Signal Processing, which is available online. And for a music background, I'd recommend: Bill Sethares' Tuning, Timbre,...
Peter K.'s user avatar
  • 25.7k
3 votes

Is there a program to extract features from an audio signal?

The openSMILE audio feature extraction toolkit may be able to provide the functionality you desire, where the input is a .wav file and the output extracted audio features. See: http://audeering.com/...
user3898238's user avatar
3 votes

Palm Pilot Graffiti

Surprised? DARPA (GRAIL project?, et.al.) supported handwriting recognition research circa 3 decades earlier, and on mainframes less powerful than a PalmPilot 1000. Hawkins talks a bit about ...
hotpaw2's user avatar
  • 35.3k
3 votes

Down sampling an EEG signal

Merely downsampling will result in a loss of information, unless you know the data of interest lives in a particular frequency band which you can filter down to. To determine that, you should look at ...
Gillespie's user avatar
  • 1,767
3 votes

What are features in signal processing using a more tangible or less abstract description

A feature is a number that describes one aspect of a signal. Signals can be very complex, and the simplest analysis tools (like a time plot, a spectrum, or an energy measurement) don't tell you ...
MBaz's user avatar
  • 15.3k
3 votes
Accepted

Anonymize / Obfuscate speech when doing audio classification

If I only use the images of power spectrograms are those images obfuscated enough to make a reconstruction of the audio signal not feasible? That depends on how you parameterize your spectrogram. In ...
Marcus Müller's user avatar
2 votes

Feature Vector from an audio signal

Have a good read of various features that can be extracted from popular audio analysis libraries like librosa: https://librosa.github.io/librosa/feature.html Fundamental frequency (F0) can definitely ...
ruoho ruotsi's user avatar
  • 1,770
2 votes
Accepted

How signal moments work?

I dont think there is a common framework for defining all those operators. Each of them were developed by different people, at several moments of the history. They are being integrated day by day onto ...
Brethlosze's user avatar
  • 1,430
2 votes

Using Convolution as Feature Extraction

Your understanding of the convolution process is correct. However, note that in the convolution the kernel is first mirrored before the dot product. Though, for a symmetric kernel this does not matter....
Maximilian Matthé's user avatar
2 votes
Accepted

What is the use of perception calculation in Speaker Identification?

Well, I don't know whether it'll actually help you – you just said it would! Now, in any case, using an algorithm to extract features from a signal that mimics or resembles human perception should ...
Marcus Müller's user avatar
2 votes

feature selection for classification for rare classes

Try one of Arizona State - Feature Selection Algorithms for feature selection: ...
Sofiane's user avatar
  • 178
2 votes

How to extract prosodic cues from a wav file using Python

This project Speech Signal Processing Toolkit (SPTK) provides several features you are looking for. Here is a good wrapper around it https://github.com/r9y9/pysptk This wrapper is using a slightly ...
Rachid Riad's user avatar
2 votes

Palm Pilot Graffiti

It seems most of the data is in Graffiti (Palm OS) - Wikipedia. It seems the technology is related to Unistrokes technology (U.S. Patent 5,596,656, granted in 1997). Since the model relies on single ...
Royi's user avatar
  • 19.6k
2 votes

Why is LPCC and LPC used in speech recognition

I think a high-level explanation is the right thing to give here: For recognition of a producing process (in this case: speech) from a signal (in this case: audio), you need to find a mapping from ...
Marcus Müller's user avatar
2 votes
Accepted

Features Used for Instrument Recognition?

Well the state of the art performance on such tasks is achieved by deep neural networks, and especially, the convolutional ones (CNNs) set you free of extracting hand crafted features. The network ...
Tolga Birdal's user avatar
  • 5,465
2 votes
Accepted

What is the purpose of dividing an audio signal into segments and analysis each segment?

Analyzing signals per segments, with proper windowing, is a way to cope with non-stationary in audio samples. With full-size analysis, features can get mixed. Segment-splitting is thus at play in ...
Laurent Duval's user avatar
2 votes

Working with a sound's magnitude instead of amplitude

There is no reason why your piezo shouldn't be able to produce a bipolar output, if you use proper biasing and/or preamp. See for example https://www.homemade-circuits.com/diy-contact-mic-circuit/ ...
Hilmar's user avatar
  • 44.7k
2 votes

Accurate phase calculation in sinusoidal linear regression?

Do an FFTShift (rotate the data halfway) before doing an FFT for phase analysis. That will re-reference the measured phase to the center of your data, not to potential circular discontinuities at the ...
hotpaw2's user avatar
  • 35.3k
2 votes
Accepted

Why is scaling of images / pixels into `[0, 1]` range performed before SIFT (Scale Invariant Feature Transform) algorithm?

Scaling images into the [0, 1] range makes many operations more natural when using images. It also normalizes hyper parameters such as threshold independently of ...
Royi's user avatar
  • 19.6k
2 votes

Extract diagonal area from image

1.- Input image and fix contrast A=imread('001.jpg'); 3 layers RGB to single layer Y: ...
John Bofarull Guix's user avatar
2 votes
Accepted

Short time energy or root mean square?

RMS $$\sqrt{\frac{1}{N}\sum_{n_0}^{n_0+N}x^2[n]}$$ STE $$\sum_{n_0}^{n_0+N}x^2[n]$$ So there's little difference except the RMS is an average value, and the square root converts the values back to ...
Jdip's user avatar
  • 6,055
2 votes
Accepted

How to feed multi-channel spectrograms to Deep Neural Network?

Concatenation is how this is usually handled, but usually you view your data a as a stack of spectrograms. If you have C channels each with, then for each channel ...
Bob's user avatar
  • 2,373
1 vote

How to Describe the Color of an Image Patch?

Another approach which might be appropriate in your Bayesian approach (Filter Particle) would be Mean Vector + Covariance Matrix. Even for that you could employ your idea of weighing (Which is ...
Royi's user avatar
  • 19.6k

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