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import soundfile as sf
import numpy as np
from scipy import signal
from pydub import AudioSegment
import subprocess
import os
# ref. Hirst The analysis by synthesis of speech melody: from data to models
# reaper requires wav file path input,
# not audio data itself.
# reaper does NOT require 16khz mono audio.
def reaper_soundfile(sound_path, orig_filetype):
aud_data = AudioSegment.from_file(sound_path, orig_filetype)
curdir = subprocess.run(["pwd"], capture_output=True, text=True)
curdir = curdir.stdout.splitlines()[0]
fname = sound_path.split('/')[-1].replace(orig_filetype,'')
tmp_path = f'{curdir}/REAPER_TMP/{fname}_tmp.wav'
if not os.path.exists(f'{curdir}/REAPER_TMP'):
os.mkdir(f'{curdir}/REAPER_TMP')
aud_data.export(tmp_path, format="wav")
wav_path = tmp_path
return wav_path
def get_reaper(wav_path, maxf0='700', minf0='50', reaper_path = "REAPER/build/reaper"):
f0_data = subprocess.run([reaper_path, "-i", wav_path, '-f', '/dev/stdout', '-x', maxf0, '-m', minf0, '-a'],capture_output=True).stdout
#print('PLAIN:',f0_data)
f0_data = f0_data.decode()
#print('DECODE-PITCH:',f0_data)
f0_data = f0_data.split('EST_Header_End\n')[1].splitlines()
#print(f0_data)
f0_data = [l.split(' ') for l in f0_data]
f0_data = [l for l in f0_data if len(l) == 3] # the last line or 2 lines are other info, different format
f0_data = [ [float(t), float(f)] for t,v,f in f0_data if v=='1']
return f0_data
# 2 pass pitch estimation
def estimate_pitch(sound_path):
orig_ftype = sound_path.split('.')[-1]
if orig_ftype == '.wav':
wav_path = sound_path
else:
tmp_path = reaper_soundfile(sound_path)
wav_path = tmp_path
print('REAPER FILE PATH:', wav_path)
first_pass = get_reaper(wav_path)
first_pass = [f for t,f in first_pass]
q1 = np.quantile(first_pass,0.25)
q3 = np.quantile(first_pass,0.75)
pfloor = 0.75 * q1
pceil = 1.5 * q3
second_pass = get_reaper(wav_path,maxf0 = str(round(pceil)), minf0 = str(round(pfloor)))
if orig_ftype != '.wav':
subprocess.run(["rm", tmp_path])
return second_pass
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