2017-11-28 10:16:39 +00:00
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import pandas as pd
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2017-11-30 09:19:55 +00:00
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import numpy as np
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import random
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from functools import reduce
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from speech_pitch import *
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# %matplotlib inline
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2017-11-28 10:16:39 +00:00
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def fix_csv(collection_name = 'test'):
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seg_data = pd.read_csv('./outputs/'+collection_name+'.csv',names=['phrase','filename'
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,'start_phoneme','end_phoneme','start_time','end_time'])
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seg_data.to_csv('./outputs/'+collection_name+'.fixed.csv')
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2017-11-30 09:19:55 +00:00
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def pick_random_phrases(collection_name='test'):
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collection_name = 'test'
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seg_data = pd.read_csv('./outputs/'+collection_name+'.fixed.csv',index_col=0)
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phrase_groups = random.sample([i for i in seg_data.groupby(['phrase'])],10)
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result = []
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for ph,g in phrase_groups:
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result.append(ph)
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pd.DataFrame(result,columns=['phrase']).to_csv('./outputs/'+collection_name+'.random.csv')
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# pick_random_phrases()
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2017-11-28 10:16:39 +00:00
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2017-11-30 09:19:55 +00:00
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def plot_random_phrases(collection_name = 'test'):
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2017-11-28 13:40:19 +00:00
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collection_name = 'test'
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2017-11-30 09:19:55 +00:00
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rand_words = pd.read_csv('./outputs/'+collection_name+'.random.csv',index_col=0)
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rand_w_list = rand_words['phrase'].tolist()
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2017-11-28 10:16:39 +00:00
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seg_data = pd.read_csv('./outputs/'+collection_name+'.fixed.csv',index_col=0)
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2017-11-30 09:19:55 +00:00
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result = (seg_data['phrase'] == rand_w_list[0])
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for i in rand_w_list[1:]:
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result |= (seg_data['phrase'] == i)
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# seg_data[result]
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phrase_groups = [i for i in seg_data[result].groupby(['phrase'])]
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self_files = ['a_wrong_turn-low1.aiff','great_pin-low1.aiff'
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,'he_set_off_at_once_to_find_the_beast-low1.aiff'
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,'hound-low1.aiff','noises-low1.aiff','po_burped-low1.aiff'
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,'she_loves_the_roses-low1.aiff','the_busy_spider-low1.aiff'
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,'the_rain_helped-low1.aiff','to_go_to_the_doctor-low1.aiff']
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co_files = map(lambda x: './inputs/self/'+x,self_files)
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for ((ph,g),s_f) in zip(phrase_groups,co_files):
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# ph,g = phrase_groups[0]
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file_path = './outputs/test/'+g.iloc[0]['filename']
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phrase_sample = pm_snd(file_path)
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self_sample = pm_snd(s_f)
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player,closer = play_sound()
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# rows = [i for i in g.iterrows()]
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# random.shuffle(rows)
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print(ph)
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phon_stops = []
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for (i,phon) in g.iterrows():
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end_t = phon['end_time']/1000
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phon_ch = phon['start_phoneme']
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phon_stops.append((end_t,phon_ch))
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plot_sample_pitch(phrase_sample,phons = phon_stops)
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plot_sample_pitch(self_sample)
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# player(phrase_sample)
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# input()
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# for (i,phon) in g.iterrows():
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# # phon = g.iloc[1]
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# start_t = phon['start_time']/1000
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# end_t = phon['end_time']/1000
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# phon_ch = phon['start_phoneme']
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# phon_sample = phrase_sample.extract_part(from_time=start_t,to_time=end_t)
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# if phon_sample.n_samples*phon_sample.sampling_period < 6.4/100:
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# continue
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# # if phon_ch[0] not in 'AEIOU':
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# # continue
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# # phon_sample
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# # player(phon_sample)
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# # plot_sample_intensity(phon_sample)
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# print(phon_ch)
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# plot_sample_pitch(phon_sample)
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closer()
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# print(phg)#['start_phoneme'],g['start_time'])
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plot_random_phrases()
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