Merge branch 'master' of /home/ilml/Public/Repos/speech_scoring
commit
b267b89a44
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@ -12,9 +12,9 @@ import time
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from tqdm import tqdm
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from generate_similar import similar_phoneme_phrase,similar_phrase
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from speech_tools import hms_string,create_dir,format_filename
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from speech_tools import hms_string,create_dir,format_filename,reservoir_sample
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OUTPUT_NAME = 'story_phrases'
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OUTPUT_NAME = 'test_5_words'
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dest_dir = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '/'
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dest_file = './outputs/' + OUTPUT_NAME + '.csv'
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@ -227,7 +227,7 @@ def generate_audio_for_stories():
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text_list = sorted(list(set(text_list_dup)))
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generate_audio_for_text_list(text_list)
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def generate_test_audio_for_stories():
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def generate_test_audio_for_stories(sample_count=0):
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'''
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Picks a list of words from the wordlist that are not in story words
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and generates the variants
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@ -241,11 +241,12 @@ def generate_test_audio_for_stories():
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word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()]
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text_set = set(text_list)
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new_word_list = [i for i in word_list if i not in text_set and len(i) > 4]
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test_words = new_word_list[:int(len(text_list)/5+1)]
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# test_words = new_word_list[:int(len(text_list)/5+1)]
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test_words = reservoir_sample(new_word_list,sample_count) if sample_count > 0 else new_word_list
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generate_audio_for_text_list(test_words)
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if __name__ == '__main__':
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# generate_test_audio_for_stories()
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generate_test_audio_for_stories(5)
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# generate_audio_for_text_list(['I want to go home','education'])
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generate_audio_for_stories()
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# generate_audio_for_stories()
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@ -57,7 +57,8 @@ class Delegate (NSObject):
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'''Called automatically when the application has launched'''
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print("App Launched!")
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# phrases = story_texts()#random.sample(story_texts(), 100) #
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phrases = test_texts(30)
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# phrases = test_texts(30)
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phrases = story_words()
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# print(phrases)
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generate_audio(phrases)
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@ -174,14 +175,19 @@ class SynthesizerQueue(object):
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def story_texts():
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# story_file = './inputs/all_stories_hs.json'
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story_file = './inputs/all_stories.json'
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stories_data = json.load(open(story_file))
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# text_list_dup = [t[0] for i in stories_data.values() for t in i]
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text_list_dup = [t for i in stories_data.values() for t in i]
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text_list = sorted(list(set(text_list_dup)))
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return text_list
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def story_words():
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story_file = './inputs/all_stories_hs.json'
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stories_data = json.load(open(story_file))
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text_list_dup = [t[0] for i in stories_data.values() for t in i]
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text_list = sorted(list(set(text_list_dup)))
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return text_list
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def test_texts(count=10):
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word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()]
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text_list = sorted(random.sample(list(set(word_list)),count))
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