Is it possible to transform speech (pitch/formant shift) in (near) real-time using MATLAB? How can it be done?
If not, what should I use to do that?
I need to get input from the microphone, visualise the sound wave, add a filter to it, see the oscilloscope again, and play back the modified sound.
The real-time visualization (spectrogram) can be created with SparkNG package by Hideki Kawahara.
Sure. There's a demo application up on the MATLAB Central File Exchange that does something similar. It reads in a signal from the sound card (requires Data Acquisition Toolbox) in near real time, applies an FFT transform - you could do something else like applying a filter - and visualises the results in 3D graphs live. You could use it as a template and modify it to your needs, such as visualising in different ways (more of an oscilloscope style), or outputting the sound as a .wav file for later playback.
If you need properly real time, you might look into implementing in Simulink rather than just base MATLAB.
Related
I need to implement an LMS-based adaptive audio-cancellation algorithm on the Simulink Desktop Real-Time toolbox.
The physical system is composed of a microphone recording a noise source and another microphone recording the residual noise after the control process (antinoise being injected by a speaker controlled by Simulink).
For the (adaptive) LMS algorithm to work properly I need to be able to work on a sample-by-sample basis, that is at each sampled time instant I need to update the adaptive filter using the synchronised current sample value of both microphones. I realise some delay is inevitable but I was wondering whether it's possible on Simulink Desktop Real-Time to reduce the buffer size of the inputs to one sample and thus work on a sample-by-sample basis.
Thanks for your help in advance.
You can always implement the filter on a sample by sample basis.
But you still need a history of input values to perform the actual LMS calculation on. On a sample by sample basis this would just mean using a simple FIFO buffer.
If you have access to the DSP Toolbox then there is already an LMS Filter block that will do this for you.
I'm looking at an output of an electroencephalogram sensor. This data is displayed on screen in raw form at about 200Hz. I read that in the old times, it was possible to hook up such output to a speaker and hear the waveform, instead of seeing it. So I'm interested if it is possible to replicate this experiment with modern iPhone. How can I take a waveform that is displayed in a graph form and package it in such a way that it can be played through a iPhone's speakers live? In other words, I'm looking to stream EEG data through some sort of audio player and need to know how to create audio packets from this data on the fly.
Here's the raw waveform, it is displayed at 200 data points per second (200Hz)
After I clean up and process the waveform, I'm interested in how far it deviates from the average of the waveform. In this case, I think this can be played as a increasing/decreasing amplitude of a sine wave, which may be easier.
Thank you for your input
Here's a good tutorial on generating a sine tone for output through CoreAudio:
http://www.cocoawithlove.com/2010/10/ios-tone-generator-introduction-to.html
The RenderProc is the bit of code you're twiddling with, in the example they're using an NSSlider to change the frequency, you just need to feed it with your signal data instead.
One of the ideas that I had for playing sound in response to the signal amplitude change is to divide the amplitude into a set of discrete bands of values (for example 0-10, 10-20, 20-30, etc) and then assign a sound to each band. Then using audio services or system sound, it might be possible to loop a unique sound fragment for each band.
I have a multimedia file block in Simulink, and I'm using it to play out of my speakers. It's working fine, but I'm wondering if there's a way to extract the signal in MATLAB using get_param or something similar. I want to plot the entire signal on a GUI, so I need to have the entire signal before I play it.
I ended up using a dsp.AudioFileReader to read my song. Not even bothering with the from Multimedia File, because I don't know how to get the entire signal from that quickly (it outputs at the sampling rate, I wanted to plot the signal before playing the song).
I created a while loop and stepped through the dsp.AudioFileReader quickly enough and then played my song through the multimedia block.
Can you connect your multimedia block to a 'To File' or a 'To Workspace' block? That would save the signal to a file that you could later load in, or directly to a workspace variable. You could then plot it, or incorporate it into your GUI, within MATLAB.
I have no experience in MATLAB and unfortunately my project is in MATLAB.
Basically the objective is to read a music source (preferably in mp3 format but .wav is also OK) into MATLAB and then apply a low pass filter in such a way that it filters everything except the beats. Then it should get the time at which each beat occurs and write the results to a text file.
It's quite a bit easier to work with .wav files I think, although Matlab way well have utilities for such things, in fact it does: Reading .wav
The easiest way to implement a low pass filter is a moving average filter.
The simplest way to do this would be be to loop over the data and take an average of each group of n values. I'm not sure exactly how the cutoff frequency would depend on n, but you could experiment a bit.
Otherwise, I know that there is a signal processing toolkit for Octave and I think that Matlab has a built-in filter function: https://ccrma.stanford.edu/~jos/fp/Matlab_Filter_Implementation.html
A third way which is over the top, would be to perform an FFT and do the filtering in the frequency domain.
Once you have the low-frequency part of the signal you can check for samples that are above an amplitude threshold and output where in the data these were found.
30 seconds on google with the keywords "beat extraction matlab" yield the following two code sources:
Music Audio Tempo Estimation and Beat Tracking
Beat This A Beat Synchronization Project
In Matlab you can use and state of the art Multi Feature beat tracker algorithm, the information of the algorithm is publish here:
J.R. Zapata, M. Davies and E. Gómez, "Multi-feature beat tracker," IEEE/ACM Transactions on Audio, Speech and Language Processing. 22(4), pp. 816-825, 2014. http://dx.doi.org/10.1109/TASLP.2014.2305252
The Matlab implementation of the multifeature beat tracker is:
https://github.com/JoseRZapata/MultiFeatureBeatTracking
I was looking to implement voice pitch detection in iphone using HPS method. But the detected tones are not very accurate. Performous does a decent job of pitch detection.
I looked through the code but i did not fully get the theory behind the calculations.
They use FFT and find the peaks. But the part where they use the phase of FFT output, got me confused.I figure they use some heuristics for voice frequencies.
So,Could anyone please explain the algorithm used in Performous to detect pitch?
[Performous][1] extracts pitch from the microphone. Also the code is open source. Here is a description of what the algorithm does, from the guy that coded it (Tronic on irc.freenode.net#performous).
PCM input (with buffering)
FFT (1024 samples at a time, remove 200 samples from front of the buffer afterwards)
Reassignment method (against the previous FFT that was 200 samples earlier)
Filtering of peaks (this part could be done much better or even left out)
Combining peaks into sets of harmonics (we call the combination a tone)
Temporal filtering of tones (update the set of tones detected earlier instead of simply using the newly detected ones)
Pick the best vocal tone (frequency limits, weighting, could use the harmonic array also but I don't think we do)
I still wasn't able from this information to figure it out and implement it. If anyone manages this, please please post your results here, and comment this response so that SO notifies me.
The task would be to create a minimal C++ wrapper around this code.