def test_basic(praatpath):
    basic_script = 'echo hello'

    pl = PraatLoader(praatpath = praatpath, basic = basic_script, debug = True)

    text = pl.run_script('basic')
    assert(text == 'hello')
Example #2
0
def test_basic(praatpath):
    basic_script = 'echo hello'

    pl = PraatLoader(praatpath=praatpath, basic=basic_script, debug=True)

    text = pl.run_script('basic')
    assert (text == 'hello')
Example #3
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def get_praat_pitch(audio_file):
    """Given a wav file, use Praat to return a dictionary containing pitch (in Hz)
    at each millisecond."""

    pl = PraatLoader(praatpath=path.abspath('Praat.app/Contents/MacOS/Praat'))
    praat_output = pl.run_script('pitch.praat', audio_file)
    pitch_data = pl.read_praat_out(praat_output)

    return pitch_data
Example #4
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def get_praat_pitch(audio_file):
    """Given a wav file, use Praat to return a dictionary containing pitch (in Hz)
    at each millisecond."""

    pl = PraatLoader(praatpath=path.abspath('Praat.app/Contents/MacOS/Praat'))
    praat_output = pl.run_script('pitch.praat', audio_file)
    pitch_data = pl.read_praat_out(praat_output)

    return pitch_data
def praat_analyze_pitch(audio_file):
	"""Given a wav file, use Praat to return a dictionary containing pitch (in Hz)
	at each millisecond."""

	praatpath = path.abspath('Praat.app/Contents/MacOS/Praat')	# locate Praat executable
	pl = PraatLoader(praatpath=praatpath)	# create instance of PraatLoader object
	
	praat_output = pl.run_script('pitch.praat', audio_file)	# run pitch script in Praat
	pitch_data = pl.read_praat_out(praat_output) # turn Praat's output into Python dict

	return pitch_data
    def _檢查查甫查某(cls, 檔名):
        pl = PraatLoader()
        音懸結果 = pl.run_script('pitch.praat', 檔名)
        查某 = 0
        查甫 = 0
#         print(檔名, 音懸結果)
        for 資料 in pl.read_praat_out(音懸結果).values():
            音懸 = 資料['Pitch']
            if 音懸 != 0:
                if 音懸 > cls.查某查甫音懸門檻:
                    查某 += 1
                else:
                    查甫 += 1
        # 一個0.001秒
        if 查某 + 查甫 <= 50:
            return None
        if 查某 >= 查甫:
            return '查某'
        return '查甫'
Example #7
0
from praatinterface import PraatLoader

pl = PraatLoader(praatpath = '/usr/bin/praat')

in_dir = '/home/pi/Documents/Project_Jammin/speech_emotion_classifier/wav/wav/carlos/casa_may_24_2016'
#in_dir = '/home/pi/Documents/Project_Jammin/speech_emotion_classifier/test'
out_dir = '/home/pi/Documents/Project_Jammin/speech_emotion_classifier/vectors/carlos/casa_may_24_2016/mfcc'
#out_dir = '/home/pi/Documents/Project_Jammin/speech_emotion_classifier/vectors/live'
text = pl.run_script('/home/pi/Documents/Project_Jammin/speech_emotion_classifier/wav2mfcc.praat', in_dir, out_dir )
#text = pl.run_script('/home/pi/Documents/Project_Jammin/speech_emotion_classifier/formants.praat','/home/pi/Documents/Project_Jammin/speech_recognition/wav/test.wav', 5500, 5)

print text
mats = pl.read_praat_out(text)
print mats
print "Done"
Example #8
0
# define important directories here
trainpath = '/home/ashu/Desktop/emotion/hack-the-talk-exotel/training_dataset'
temppath = '/home/ashu/Desktop/emotion/hack-the-talk-exotel/temp'
praatpath = '/usr/bin/praat'

sound = AudioSegment.from_mp3("one.mp3")
print('imported...')

# slicing necessary as program gets stuck with long files
# we can find out optimal length and then work with it in a loop
# lets extend this script to extract features for all files and save them
# in some format
song = sound[:1000]
song.export("one.wav", format="wav")
print('exported...')


praatpath = '/usr/bin/praat'
pl = PraatLoader(praatpath = praatpath, debug = True)

text = pl.run_script('formants.praat', '/home/ashu/Desktop/emotion/hack-the-talk-exotel/features/one.wav', 5, 5500)
formants = pl.read_praat_out(text)
for x in formants:
    print (x)
    for y in formants[x]:
        print (y,':',formants[x][y])
print(type(formants))
# formants is a dictionary so we can append it to create dictionary for whole time interval
# this way we have several dictionaries for several features
# we can also manipulate these dictionaries to form arrays (lists) for corresponding feature
def extract_vowel(original_file,begin,end,output_file):
    begin -= 0.025
    end += 0.025
    p = PraatLoader()
    p.run_script('extract.praat',original_file,begin,end,output_file)
def test_formants(praatpath, sound_file):
    pl = PraatLoader(praatpath = praatpath, debug = True)
    text = pl.run_script('formants.praat',sound_file, 5, 5500)

    formants = pl.read_praat_out(text)
Example #11
0
def test_formants(praatpath, sound_file):
    pl = PraatLoader(praatpath=praatpath, debug=True)
    text = pl.run_script('formants.praat', sound_file, 5, 5500)

    formants = pl.read_praat_out(text)