Waveform analysis/Doh ray me: Difference between revisions

=={{header|Julia}}==

Uses the LibSndFile library for WAV file reading and the FFTW library for FFT to try to analyze the sound for its fundamental frequency.

<lib julia>using FFTW, FileIO, LibSndFile

const soundfilename = "Cscale3octaves.wav"

const freq_to_solfa = Dict([

130.81 => "DOH"

146.83 => "RAY"

164.81 => "MEE"

174.61 => "FAH"

196.0 => "SOH"

220.0 => "LAH"

246.94 => "TEE"

261.63 => "Doh"

293.66 => "Ray"

329.63 => "Mee"

349.23 => "Fah"

392.0 => "Soh"

440.0 => "Lah"

493.88 => "Tee"

523.25 => "doh"

587.33 => "ray"

659.25 => "mee"

698.46 => "fah"

783.99 => "soh"

880.0 => "lah"

987.77 => "tee"

])

const sfreqs = sort(collect(keys(freq_to_solfa)))

function closestfreqs(samples, fs=44100.0)

pfreqs = Float64[]

for sample in samples

ff = fft(sample)

xr = div(length(sample), 2)

ffreqs = LinRange(1, fs, length(sample))

sigpow = (abs.(ff)).^2.0

fmax = ffreqs[argmax(sigpow)]

idx = argmin([abs(f - fmax) for f in sfreqs])

push!(pfreqs, sfreqs[idx])

end

return pfreqs

end

function getchunks(soundfile, channel=1, timespan=0.11)

sv = load(soundfile)

fs = LibSndFile.samplerate(sv)

samplespan, data = Int(round(timespan * fs)), view(sv, :, channel)

return (fs, [data[i:i+samplespan-1] for i in 1:samplespan:length(data)-samplespan-1])

end

function makenotelist(soundfile, fs=44100.0, repetitionsneeded=1)

changelist = String[]

fs, samples = getchunks(soundfile)

freqs = closestfreqs(samples, fs)

reps, prev = 0, ""

for freq in freqs

note = freq_to_solfa[freq]

if note != prev

prev = note

reps = 0

else

reps += 1

if reps == repetitionsneeded

push!(changelist, note)

end

end

end

return changelist

end

println(makenotelist(soundfilename))

</lang>{{out}}

<pre>

["DOH", "RAY", "MEE", "FAH", "SOH", "LAH", "TEE", "Doh", "Ray", "Mee", "Fah", "Soh", "Lah", "Lah", "Tee", "doh", "ray", "mee", "fah", "soh", "lah", "tee"]

</pre>