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The solution we came up with to alleviate this problem is to average what the program thinks is the highest frequencies across multiple frames of data. We tested out different average lengths and found that averaging every 25 frames sounded the best. Our code will keep track of a variable-length list that contains the frequency of the highest peak per frame. At the start of every frame a new frequency value will be added to the list, and at the end of every frame the list is averaged to determine a single frequency. This list resets every 25 frames. In midst of this process, we also converted to linear frequency from FFT bins, which is done by multiplying by the ratio of the sampling frequency over half the chunk length. To further improve our results, we only added to the list frequencies if the magnitude of that particular frequency bin is above a particular value. This way our code will ignore the low amplitude noise and only record frequencies when a note is being played.

flag = 0 freq = []while(True): data = stream.read(CHUNK)x = numpy.fromstring(data, dtype=numpy.float32) x_filtered = scipy.signal.lfilter(taps, 1.0, x)X = numpy.fft.fft(x_filtered) highest_freq = numpy.argmax(abs(X[0:511]))flag +=1 if (X[highest_freq]>5000): freq.append(highest_freq*44100/(CHUNK/2))avg = (sum(freq)/len(freq)) if flag == 25:flag = 0freq = []

Creating the harmony

Once we have the correct frequency and the identity of the note, we proceed to figure out the frequency of the harmonizing note. We first create a Python dictionary of musical keys mapped to a list of the corresponding frequencies of that note at different octaves. For purposes of demonstration, we only added the key of C to the dictionary. However, other keys could easily be added. We then created a function that helps on determine which harmonic we are in given a musical key and the frequency of a note. We then apply the formula for finding the harmonizing frequencies describe in the previous section to the frequency we have and obtain the frequency of the third and fifth intervals from the note being played.

keys = {'c':[1636,1636/2,1636/4,1636/8]}sBuf = 50 def key_select(freq, key):for f in keys[key]:if freq>= f: return freturn freq def chord_freqs(key, note):n = 1200*numpy.log2(note/key) if(500-sBuf<= n<=500+sBuf or 700-sBuf<= n<=700+sBuf or n<=sBuf): f3 = note * math.pow(2, (400)/1200)f5 = note * math.pow(2, (700)/1200) return f3 , f5elif (200-sBuf<n<200+sBuf or 400-sBuf<n<400+sBuf or 900-sBuf<n<900+sBuf): f3 = note * math.pow(2, (300)/1200)f5 = note * math.pow(2, (700)/1200) return f3, f5elif (1100-sBuf<n<1100+sBuf): f3 = note * math.pow(2, (300)/1200)f5 = note * math.pow(2, (600)/1200) return f3, f5else: return 0,0

After obtaining the two harmony frequencies, we tried to take them into the time domain. We initially tried add triangles of frequency content centered at the desired frequencies and then taking the inverse transform, in hope to try to mimic a "real" sound. However, doing that caused the note to sound slightly off. Also we didn't add imaginary components to the frequency and the FFT library gave us warnings. So we decided to try out other approaches. The next thing we thought of was using the Karplus-Strong Plucked String algorithm to create a realistic decaying note. But we very quickly saw that the algorithm was not really meant to be used in real time. The algorithm works by creating the complete decaying signal. However, this is problem with other stream because we can only output 1024 samples at a time, which is not long enough to squeeze the whole decay in. We thought about storing the whole signal from the Plucked String algorithm and output it a frame at a time. But doing so not only slow down our system, but also would introduce problems if we played a different note half way through a output decaying note. We ended up deciding to just output pure sine waves and worry about making it sound less synthesized in the future.

def play_tone(stream, frequency=252, length=1, rate=44100): chunks = []f3 , f5 = chord_freqs(key_select(frequency, 'c'), frequency) chunks.append(sine(f3, length, rate)+sine(f5, length, rate))chunk = numpy.concatenate(chunks) * 0.25 stream.write(chunk.astype(numpy.float32).tostring(), CHUNK)def sine(frequency, length, rate): length = int(length * rate)factor = float(frequency) * (numpy.pi * 2) / rate return numpy.sin(numpy.arange(length) * factor)

Now that we were only outputting pure sine waves, we decided that it would be faster and save computation complexity but just creating the sine waves of the correct frequencies in the time domain directly. This would save computation time as now we don't need to compute an inverse FFT. To put it all together. We output the harmonies through the PyAudio stream. The UCA222 takes this and adds it to the guitar signal that it is already forwarding to the speakers.

Questions & Answers

Is there any normative that regulates the use of silver nanoparticles?
Damian Reply
what king of growth are you checking .?
What fields keep nano created devices from performing or assimulating ? Magnetic fields ? Are do they assimilate ?
Stoney Reply
why we need to study biomolecules, molecular biology in nanotechnology?
Adin Reply
yes I'm doing my masters in nanotechnology, we are being studying all these domains as well..
what school?
biomolecules are e building blocks of every organics and inorganic materials.
anyone know any internet site where one can find nanotechnology papers?
Damian Reply
sciencedirect big data base
Introduction about quantum dots in nanotechnology
Praveena Reply
what does nano mean?
Anassong Reply
nano basically means 10^(-9). nanometer is a unit to measure length.
do you think it's worthwhile in the long term to study the effects and possibilities of nanotechnology on viral treatment?
Damian Reply
absolutely yes
how to know photocatalytic properties of tio2 nanoparticles...what to do now
Akash Reply
it is a goid question and i want to know the answer as well
characteristics of micro business
for teaching engĺish at school how nano technology help us
Do somebody tell me a best nano engineering book for beginners?
s. Reply
there is no specific books for beginners but there is book called principle of nanotechnology
what is fullerene does it is used to make bukky balls
Devang Reply
are you nano engineer ?
fullerene is a bucky ball aka Carbon 60 molecule. It was name by the architect Fuller. He design the geodesic dome. it resembles a soccer ball.
what is the actual application of fullerenes nowadays?
That is a great question Damian. best way to answer that question is to Google it. there are hundreds of applications for buck minister fullerenes, from medical to aerospace. you can also find plenty of research papers that will give you great detail on the potential applications of fullerenes.
what is the Synthesis, properties,and applications of carbon nano chemistry
Abhijith Reply
Mostly, they use nano carbon for electronics and for materials to be strengthened.
is Bucky paper clear?
carbon nanotubes has various application in fuel cells membrane, current research on cancer drug,and in electronics MEMS and NEMS etc
so some one know about replacing silicon atom with phosphorous in semiconductors device?
s. Reply
Yeah, it is a pain to say the least. You basically have to heat the substarte up to around 1000 degrees celcius then pass phosphene gas over top of it, which is explosive and toxic by the way, under very low pressure.
Do you know which machine is used to that process?
how to fabricate graphene ink ?
for screen printed electrodes ?
What is lattice structure?
s. Reply
of graphene you mean?
or in general
in general
Graphene has a hexagonal structure
On having this app for quite a bit time, Haven't realised there's a chat room in it.
what is biological synthesis of nanoparticles
Sanket Reply
how did you get the value of 2000N.What calculations are needed to arrive at it
Smarajit Reply
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Source:  OpenStax, Harmonizing guitar pre-amp. OpenStax CNX. Dec 15, 2015 Download for free at http://legacy.cnx.org/content/col11932/1.4
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