87 lines
2.6 KiB
Python
87 lines
2.6 KiB
Python
import json
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from converter import TranscriptConverter
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import helpers
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class AmazonConverter(TranscriptConverter):
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def __init__(self, path, output_target):
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super().__init__(path, output_target)
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def get_word_objects(self, json_data):
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return json_data['results']['items']
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def get_words(self, word_objects):
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return [self.get_word_word(w)
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for w in word_objects]
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@staticmethod
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def get_word_start(word_object):
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return float(word_object['start_time'])
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@staticmethod
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def get_word_end(word_object):
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return float(word_object['end_time'])
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@staticmethod
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def get_word_confidence(word_object):
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return float(word_object['alternatives'][0]['confidence'])
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@staticmethod
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def get_word_word(word_object):
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word_word = word_object['alternatives'][0]['content']
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if word_word == 'i':
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# weird Amazon quirk
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word_word = 'I'
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return word_word
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def convert_words(self, word_objects, words, tagged_words=None):
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converted_words = []
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punc_before = False
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punc_after = False
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num_words = len(words)
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index = 0
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for i, w in enumerate(word_objects):
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if w['type'] == 'punctuation':
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continue
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next_word_punc_after = None
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word_obj = self.get_word_object(w, i, tagged_words, word_objects)
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if word_obj.next_word:
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next_word = self.get_word_word(word_obj.next_word)
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next_word_type = word_obj.next_word['type']
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if next_word in ['.', ',']:
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punc_after = next_word
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elif next_word_punc_after:
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punc_after = next_word_punc_after
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next_word_punc_after = None
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if word_obj.word.lower() == 'you' and next_word == 'know':
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prev_word = word_objects[i - 1]
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if prev_word['type'] != 'punctuation':
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converted_words[-1]['punc_after'] = ','
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if next_word_type != 'punctuation':
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next_word_punc_after = ','
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converted_words.append({
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'start': word_obj.start,
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'end': word_obj.end,
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'confidence': word_obj.confidence,
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'word': word_obj.word,
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'always_capitalized': (
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word_obj.is_proper_noun
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or word_obj.word == 'I'),
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'index': index,
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'punc_after': punc_after,
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'punc_before': punc_before,
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})
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index += 1
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punc_after = False
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return converted_words
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