I'm using AudioQueue to get recording level meter via microphone. The problem is what I got from it are floating point numbers. I know they represents for audio sample.
I need to convert it to Hz. My assignment is to convert a digital signal audio recording from microphone. Convert it to Hz and do a simple formula to get a result that relevant to this number.
Please help, I really appreciate your help.
Thanks,
Quan
An audio recording from a microphone will not contain a single frequency that you can represent in Hz.
Instead, it will be a combination of a lot of different frequencies mixed together, which are represented by your samples.
To get the frequencies in your sample and their amplitude, you need to use the Fast Fourier transform. From the results you can determine which frequencies are most prevalent in your sample, which I believe is what you are looking for.
Related
I'm doing a project studying rats who squeak in the ultrasonic range (20kHz to 100kHz) using Matlab software and sound files.
I have (or will be getting) a couple .wav audio signals of these rats speaking, and among general analysis of these wave forms, I also want to convert these ultrasonic signals (outside of our hearing), into the human audible range (20hz to 20khz).
Could I get some advice on how to do this conversion (via Matlab programming and not by using equipment)
Looking into this, I've found names such as:
-frequency division
-heterodyning
-envelope detection
-time expansion
but looking into these it seems either they are explained in terms of what the equipment (bat detectors) does, or they sound incredibly similar to each other. e.g. frequency division and time expansion both involve dividing the incoming signal by 10
since I am looking into what seems to be unfamiliar turf, it would be great to find multiple ways to convert the signal (to my knowledge the names above have their own associated positive and negative traits)
Your question is a signal processing question more than a Matlab question, which isn't really what Stack Overflow is about, so you might get some negative votes.
There are indeed a number of methods of changing the frequency of audio (or any signals):
1) Slow it Down: The least disruptive to the signal is simply to slow down the audio. If you are looking to have rat signals up to 100 kHz, you'll need to sample the audio at 200 kHz or greater. Once you have your recording, simply re-save the wav file telling it that the sample rate is 44.1 kHz (or whatever). This will play it more slowly, but all the frequencies will now be audible (unlike the single side band demodulation discussed below). This is definitely the place you should start...it's the easiest and will sound the best.
fs = 200e3; %your original sample rate
myAudio = load('myFile.mat'); %your original audio
fs = 44.1e3; %simply declare that you want a lower sample rate
wavwrite(myAudio,fs,16,'myFile_44kHz.wav'); %save it out at the new rate
2) Single-Side Band: Use the demod command to "demodulate" the signal to lower its frequency. There are a number of demodulation methods available with this command. I'd use "single side band (suppressed carrier)" because that is how the rat itself (and humans) create sound. To do the demodulation, you'll have to assume a "carrier frequency", as if it were a radio signal. If the lowest frequency of a rat squeek is 20 kHz, you can assume a carrier of 20 kHz. This operation will shift all of your audio down by 20 kHz. As a result the squeek that was originall 20-100 kHz, will now be 0-80 kHz. So, you won't hear the whole thing, but you'll hear part of it.
fs = 200e3; %your original sample rate
myAudio = load('myFile.mat'); %your original audio
[b,a]=butter(2,20e3/(fs/2),'high'); %define highpass filter
myAudio = filtfilt(b,a,myAudio); %remove the low frequencies
myAudio = demod(myAudio,20e3,fs,'amssb'); %shift it down 20 kHz
wavwrite(myAudio,fs,16,'myWave_shifted.wav'); %save it out
3) Phase Vocoder (or other Pitch Shifting): To hear the whole 20-100 kHz range (which is 80 kHz bandwidth, which is 4x bigger than the 20 kHz bandwidth of human hearing), you've got to go to more extreme methods. These methods will make the audio sound bizarre, but you can give it a try. There are several algorithms. Look up "phase vocoder". Or, use one of audio processing software packages like Audacity, Raven, etc.
I want to know the frequency of data. I had a little bit idea that it can be done using FFT, but I am not sure how to do it. Once I passed the entire data to FFT, then it is giving me 2 peaks, but how can I get the frequency?
Thanks a lot in advance.
Have a look at this page for an explanation on how to calculate it:
FFT Fundamentals
Please also check this answer (it's C# code but I think you can easily understand it)
How do I obtain the frequencies of each value in an FFT?
And finally have a look at this one, it uses DFT instead of FFT:
Determining the magnitude of a certain frequency on the iPhone
I also found this implementation that you can use in Objective-C:
A lib to find the frequency https://github.com/jkells/sc_listener
A example using the above library https://github.com/jkells/sc_listener_sample
Regards
An FFT will give you the frequency of all the sinusoidal components of a signal. If instead you want just the frequency of the periodicity of common waveforms (more interesting sounding and looking that a plain sinewave) such as produced by speech and music, then you may want to use a pitch detection/estimation algorithm instead of just an FFT peak.
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.
In my app, I want to find/calculate the audio frequency as dynamically when i am recording an audio and no need to save, play and all. Now i am trying to do that with help of an aurioToch sample code. In that sample, inside FFTBufferManager class methods such as GrabAudioData and ComputeFFT,Here I am not able to find where they are calculating frequency value as dynamically depends on the audio sound and I spent more than 5 days.please help me.
You don't need to use FFT if your audio signal is clear and pure. Just count the peaks and valleys. Or just peaks. Take that number and divide by the number of samples in your buffer, and then multiply by the sample rate. That's your frequency value.
I am new to iphone development.I am doing research on voice recording in iphone .I have downloaded the "speak here " sample program from Apple.I want to determine the frequency of my voice that is recorded in iphone.Please guide me .Please help me out.Thanks.
In the context of processing human speech, there's really no such thing as "the" frequency.
The signal will be a mix of many different frequencies, so it might be more fruitful to think in terms of a spectrum, rather than a single frequency. Even if you're talking about
a sustained musical note with a fixed pitch, there will be plenty of overtones and harmonics present, in addition to the fundamental frequency of the note. And for actual speech,
the frequency spectrum will change drastically even within a short clip, due to the different tonal characteristics of vowels and consonants.
With that said, it does make some sense to consider the peak frequency of a voice recording.
You could calculate the Fast Fourier Transform of your voice clip, then find the frequency
bin with the largest response. You may also be interested in the concept of a spectrogram, which represents how the audio spectrum of a signal varies over time.
Use Audacity. Take a small recording of typical speech, and cut it down to one wavelength, from one peak to another peak. Subtract the two times, and divide 1 by that number and you'll get the frequency of your wave in Hz.
Example:
In my audio clip, my waveform runs from 0.0760 to 0.0803 seconds.
0.0803-0.0760 = 0.0043
1/0.0043 = 232.558 Hz, my typical speech frequency
This might give you a good basis to create an analyzer. You'd need to detect the peaks, and time between the peaks of the wave and do an average calculation of the result.
You'll need to use Apple's Accelerate framework to take an FFT of the relevant audio. The FFT will convert the audio in the time domain to the frequency domain. The Accelerate framework supports the FFT and will allow you to do frequency analysis in real-time.