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speech-scoring
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Merge branch 'master' of /home/ilml/Public/Repos/speech_scoring

master
Malar Kannan 2017-12-29 13:15:51 +05:30
parent eb10b577ae ee2eb63f66
commit b267b89a44
2 changed files with 16 additions and 9 deletions
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13
speech_samplegen.py
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@ -12,9 +12,9 @@ import time
from tqdm import tqdm from tqdm import tqdm
from generate_similar import similar_phoneme_phrase,similar_phrase from generate_similar import similar_phoneme_phrase,similar_phrase
from speech_tools import hms_string,create_dir,format_filename from speech_tools import hms_string,create_dir,format_filename,reservoir_sample
OUTPUT_NAME = 'story_phrases' OUTPUT_NAME = 'test_5_words'
dest_dir = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '/' dest_dir = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '/'
dest_file = './outputs/' + OUTPUT_NAME + '.csv' dest_file = './outputs/' + OUTPUT_NAME + '.csv'
@ -227,7 +227,7 @@ def generate_audio_for_stories():
text_list = sorted(list(set(text_list_dup))) text_list = sorted(list(set(text_list_dup)))
generate_audio_for_text_list(text_list) generate_audio_for_text_list(text_list)
def generate_test_audio_for_stories(): def generate_test_audio_for_stories(sample_count=0):
''' '''
Picks a list of words from the wordlist that are not in story words Picks a list of words from the wordlist that are not in story words
and generates the variants and generates the variants
@ -241,11 +241,12 @@ def generate_test_audio_for_stories():
word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()] word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()]
text_set = set(text_list) text_set = set(text_list)
new_word_list = [i for i in word_list if i not in text_set and len(i) > 4] new_word_list = [i for i in word_list if i not in text_set and len(i) > 4]
test_words = new_word_list[:int(len(text_list)/5+1)] # test_words = new_word_list[:int(len(text_list)/5+1)]
test_words = reservoir_sample(new_word_list,sample_count) if sample_count > 0 else new_word_list
generate_audio_for_text_list(test_words) generate_audio_for_text_list(test_words)
if __name__ == '__main__': if __name__ == '__main__':
# generate_test_audio_for_stories() generate_test_audio_for_stories(5)
# generate_audio_for_text_list(['I want to go home','education']) # generate_audio_for_text_list(['I want to go home','education'])
generate_audio_for_stories() # generate_audio_for_stories()

12
speech_segmentgen.py
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@ -57,7 +57,8 @@ class Delegate (NSObject):
'''Called automatically when the application has launched''' '''Called automatically when the application has launched'''
print("App Launched!") print("App Launched!")
# phrases = story_texts()#random.sample(story_texts(), 100) # # phrases = story_texts()#random.sample(story_texts(), 100) #
phrases = test_texts(30) # phrases = test_texts(30)
phrases = story_words()
# print(phrases) # print(phrases)
generate_audio(phrases) generate_audio(phrases)
@ -174,14 +175,19 @@ class SynthesizerQueue(object):
def story_texts(): def story_texts():
# story_file = './inputs/all_stories_hs.json'
story_file = './inputs/all_stories.json' story_file = './inputs/all_stories.json'
stories_data = json.load(open(story_file)) stories_data = json.load(open(story_file))
# text_list_dup = [t[0] for i in stories_data.values() for t in i]
text_list_dup = [t for i in stories_data.values() for t in i] text_list_dup = [t for i in stories_data.values() for t in i]
text_list = sorted(list(set(text_list_dup))) text_list = sorted(list(set(text_list_dup)))
return text_list return text_list
def story_words():
story_file = './inputs/all_stories_hs.json'
stories_data = json.load(open(story_file))
text_list_dup = [t[0] for i in stories_data.values() for t in i]
text_list = sorted(list(set(text_list_dup)))
return text_list
def test_texts(count=10): def test_texts(count=10):
word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()] word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()]
text_list = sorted(random.sample(list(set(word_list)),count)) text_list = sorted(random.sample(list(set(word_list)),count))