727 lines
20 KiB
Python
727 lines
20 KiB
Python
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import os
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import sys
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import docx
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import re
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from tqdm import tqdm
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from collections import Counter
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import ntpath
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from docx.shared import Inches, Cm, Pt
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from docx.enum.text import WD_ALIGN_PARAGRAPH
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from docx.enum.table import WD_TABLE_ALIGNMENT, WD_ALIGN_VERTICAL
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import requests, uuid, json
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import nltk.translate.bleu_score as bleu
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import nltk.translate.gleu_score as gleu
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from rouge_score import rouge_scorer
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import numpy as np
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import statistics
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from statistics import mode
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from indicnlp.tokenize import sentence_tokenize
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import nltk
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try:
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print("time1111")
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nltk.data.find("tokenizers/punkt")
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except LookupError:
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#nltk.download("punkt")
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pass
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try:
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nltk.data.find("wordnet")
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except LookupError: ###nltk.download('wordnet')
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print("pass")
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from nltk.tokenize import sent_tokenize
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# import logging
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# from logger import get_module_logger
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# log = get_module_logger(__name__)
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# log.info('Logger working')
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# google
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os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "My First Project-2573112d5326.json"
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from google.cloud import translate
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from google.cloud import translate_v2 as Translate
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translate_client = Translate.Client()
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client = translate.TranslationServiceClient()
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project_id = "authentic-bongo-272808"
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location = "global"
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parent = f"projects/{project_id}/locations/{location}"
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from script_detector import script_cat
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from buck_2_unicode import buck_2_unicode
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from translation_metric import (
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manual_diff_score,
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bleu_diff_score,
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gleu_diff_score,
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meteor_diff_score,
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rouge_diff_score,
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diff_score,
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critera4_5,
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)
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from selection_source import (
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selection_source,
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function5,
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function41,
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function311,
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function221,
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function2111,
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function11111,
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selection_source_transliteration,
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two_sources_two_outputs,
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)
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from script_writing import (
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addSlugLine,
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addActionLine,
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addSpeaker,
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addParenthetical,
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addDialogue,
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dual_script,
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addTransition,
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dial_checker,
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non_dial_checker,
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)
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from script_reading import (
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breaksen,
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getRefined,
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getSlugAndNonSlug,
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getSpeakers,
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getScenes,
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)
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from translation_resources import ibm_watson, google, aws, azure, lingvanex, yandex
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from transliteration_resources import (
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azure_transliteration,
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indic_trans,
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om_transliterator,
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libindic,
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indic_transliteration_IAST,
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indic_transliteration_ITRANS,
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sheetal,
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ritwik,
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)
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filename1 = sys.argv[1] # original file
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non_dial_src_lang = sys.argv[2]
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non_dial_dest_lang = sys.argv[3]
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dial_src_lang = sys.argv[4]
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dial_dest_lang = sys.argv[5]
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dual_dial_script = sys.argv[6] # yes/No
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if non_dial_src_lang != non_dial_dest_lang:
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global_non_dialogue_flag = "Yes"
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else:
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global_non_dialogue_flag = "No"
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if dial_src_lang != dial_dest_lang:
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global_dialogue_flag = "Yes"
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else:
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global_dialogue_flag = "No"
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# filename1 = sys.argv[1]
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# dial_dest_lang = sys.argv[2]
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# #dial_dest_lang = user_script_data.get("dial_dest_language")
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# dial_dest_script = sys.argv[3]C:\Users\lokesh\Desktop\mnfproject1\scripts\activate
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# #dial_dest_script = user_script_data.get("dial_dest_script")
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# non_dial_dest_lang = sys.argv[4]
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# #non_dial_dest_lang = user_script_data.get("nondial_dest_language")
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# dual_dial_script = sys.argv[5]
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# #dual_dial_script = user_script_data.get("dual_dial_script") # Yes,No
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translation_list = [
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"en",
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"ta",
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"hi",
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"ar",
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"ur",
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"kn",
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"gu",
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"bg",
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"bn",
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"te",
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"ml",
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"ru",
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"sr",
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"uk",
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"hr",
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"ga",
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"sq",
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"mr",
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"fa",
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"tr",
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"hu",
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"it",
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"ro",
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"pa",
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"gu",
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"or",
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"zh",
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"ne",
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"fr",
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"es",
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"id",
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"el",
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"ja",
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"ko",
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"be",
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"uz",
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"sd",
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"af",
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"de",
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"is",
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"ig",
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"la",
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"pt",
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"my",
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"th",
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"su",
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"lo",
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"am",
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"si",
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"az",
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"kk",
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"mk",
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"bs",
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"ps",
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"mg",
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"ms",
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"yo",
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"cs",
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"da",
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"nl",
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"tl",
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"no",
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"sl",
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"sv",
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"vi",
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"cy",
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"he",
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"hy",
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"km",
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"ka",
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"mn",
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"ku",
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"ky",
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"tk",
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"he",
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"hy",
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"km",
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"ka",
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"mn",
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"ku",
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"ky",
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"tk",
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"fi",
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"ht",
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"haw",
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"lt",
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"lb",
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"mt",
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"pl",
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"eo",
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"tt",
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"ug",
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"ha",
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"so",
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"sw",
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"yi",
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"eu",
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"ca",
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"ceb",
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"co",
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"et",
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"fy",
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"gl",
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"hmn",
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"rw",
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"lv",
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"mi",
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"sm",
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"gd",
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"st",
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"sn",
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"sk",
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"xh",
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"zu",
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]
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# create an instance of a word document
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doc = docx.Document()
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doc_file = (
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"translated/"
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+ str(dial_dest_lang)
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+ "_"
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+ "trans"
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+ "_of_"
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+ ntpath.basename(filename1)
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)
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print(doc_file)
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doc1a = docx.Document()
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sections = doc1a.sections
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for section in sections:
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section.top_margin = Inches(0.2)
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section.bottom_margin = Inches(0.2)
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section.left_margin = Inches(0.2)
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section.right_margin = Inches(0.2)
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section = doc1a.sections[-1]
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new_height = section.page_width
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section.page_width = section.page_height
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section.page_height = new_height
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name = "Dialogue Comparision Table of " + doc_file
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doc1a.add_heading(name, 0)
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doc_para = doc1a.add_paragraph()
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doc_para.add_run(
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"Translation resources used : Google, IBM watson, AWS, Azure, Lingvanex, Yandex"
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).bold = True
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table1a = doc1a.add_table(rows=1, cols=4)
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table1a.style = "TableGrid"
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hdr_Cells = table1a.rows[0].cells
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hdr_Cells[0].paragraphs[0].add_run("Input").bold = True
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hdr_Cells[1].paragraphs[0].add_run("Google").bold = True
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hdr_Cells[2].paragraphs[0].add_run("MNF Diff Score Method").bold = True
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hdr_Cells[3].paragraphs[0].add_run("Bleu Diff Score Method").bold = True
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doc1b = docx.Document()
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sections = doc1b.sections
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for section in sections:
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section.top_margin = Inches(0.2)
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section.bottom_margin = Inches(0.2)
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section.left_margin = Inches(0.2)
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section.right_margin = Inches(0.2)
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section = doc1b.sections[-1]
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new_height = section.page_width
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section.page_width = section.page_height
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section.page_height = new_height
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name = "Dialogue Comparision Table of " + doc_file
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doc1b.add_heading(name, 0)
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doc_para = doc1b.add_paragraph()
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doc_para.add_run(
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"Translation resources used : Google, IBM watson, AWS, Azure, Lingvanex, Yandex"
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).bold = True
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table1b = doc1b.add_table(rows=1, cols=4)
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table1b.style = "TableGrid"
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hdr_Cells = table1b.rows[0].cells
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hdr_Cells[0].paragraphs[0].add_run("Gleu Diff Score Method").bold = True
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hdr_Cells[1].paragraphs[0].add_run("Meteor Diff Score Method").bold = True
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hdr_Cells[2].paragraphs[0].add_run("Rougen Diff Score Method").bold = True
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hdr_Cells[3].paragraphs[0].add_run("Rougel Diff Score Method").bold = True
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doc2 = docx.Document()
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sections = doc2.sections
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for section in sections:
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section.top_margin = Inches(0.2)
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section.bottom_margin = Inches(0.2)
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section.left_margin = Inches(0.2)
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section.right_margin = Inches(0.2)
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section = doc2.sections[-1]
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new_height = section.page_width
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section.page_width = section.page_height
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section.page_height = new_height
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name = "Final table " + doc_file
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doc2.add_heading(name, 0)
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doc_para = doc2.add_paragraph()
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doc_para.add_run(
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"Translation resources used : Google, IBM watson, AWS, Azure, Lingvanex, Yandex"
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).bold = True
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table2 = doc2.add_table(rows=1, cols=4)
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table2.style = "TableGrid"
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hdr_Cells = table2.rows[0].cells
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hdr_Cells[0].paragraphs[0].add_run("Input").bold = True
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hdr_Cells[1].paragraphs[0].add_run("Output1").bold = True
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hdr_Cells[2].paragraphs[0].add_run("Output2").bold = True
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hdr_Cells[3].paragraphs[0].add_run("Output3").bold = True
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# process the input script and return scenes
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refined, total_scenes = getRefined(filename1)
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print(refined)
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# log.debug(refined)
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sluglines, without_slug = getSlugAndNonSlug(refined)
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print(sluglines)
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# log.debug(sluglines)
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characters = getSpeakers(without_slug)
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# print(characters)
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# log.debug(characters)
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scenes, actionline, parenthetical_lis, speakers, dialogues = getScenes(
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refined, total_scenes, characters
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)
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# print(scenes)
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# to detect the language
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def language_detector(text):
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result = translate_client.translate(text, target_language="hi")
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det_lang = result["detectedSourceLanguage"]
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return det_lang
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class myDict(dict):
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def __init__(self):
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self = dict()
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def add(self, key, value):
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self[key] = value
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def all_translator(sentence, source_lang, target_lang):
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print("in all translator", sentence)
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# if sentence=="" or sentence==" ":
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# return
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i = 0
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trans = myDict()
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sources_name = myDict()
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try:
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globals()["t%s" % i] = google(sentence, source_lang, target_lang)
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trans.add(str(i), globals()["t%s" % i])
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sources_name.add(str(i), "GOOGLE")
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i = i + 1
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except:
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pass
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try:
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globals()["t%s" % i] = ibm_watson(sentence, source_lang, target_lang)
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trans.add(str(i), globals()["t%s" % i])
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sources_name.add(str(i), "IBM_WATSON")
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i = i + 1
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except:
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pass
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try:
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|
|
globals()["t%s" % i] = aws(sentence, source_lang, target_lang)
|
||
|
|
trans.add(str(i), globals()["t%s" % i])
|
||
|
|
sources_name.add(str(i), "AWS")
|
||
|
|
i = i + 1
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
try:
|
||
|
|
globals()["t%s" % i] = azure(sentence, target_lang)
|
||
|
|
trans.add(str(i), globals()["t%s" % i])
|
||
|
|
sources_name.add(str(i), "AZURE")
|
||
|
|
i = i + 1
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
try:
|
||
|
|
globals()["t%s" % i] = lingvanex(sentence, source_lang, target_lang)
|
||
|
|
trans.add(str(i), globals()["t%s" % i])
|
||
|
|
sources_name.add(str(i), "LINGVANEX")
|
||
|
|
i = i + 1
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
try:
|
||
|
|
globals()["t%s" % i] = yandex(sentence, source_lang, target_lang)
|
||
|
|
trans.add(str(i), globals()["t%s" % i])
|
||
|
|
sources_name.add(str(i), "YANDEX")
|
||
|
|
i = i + 1
|
||
|
|
except:
|
||
|
|
pass
|
||
|
|
|
||
|
|
# print(trans)
|
||
|
|
# print(sources_name)
|
||
|
|
|
||
|
|
trans_text = compare_outputs(sentence, trans["0"], trans, sources_name)
|
||
|
|
return trans_text
|
||
|
|
|
||
|
|
|
||
|
|
# take paragraph which returns translated paragraph by comparing translated ouptputs from different resources
|
||
|
|
|
||
|
|
|
||
|
|
def translation_with_spcecial_dots(Sentence, source_lang, target_lang):
|
||
|
|
special_characters = ["...", "…", ". . ."]
|
||
|
|
translated_text = []
|
||
|
|
|
||
|
|
for i in special_characters:
|
||
|
|
if i not in Sentence:
|
||
|
|
continue
|
||
|
|
Sentences = Sentence.split(i)
|
||
|
|
|
||
|
|
for Sentence in Sentences:
|
||
|
|
if Sentence == " " or Sentence == "":
|
||
|
|
continue
|
||
|
|
|
||
|
|
if any(ext in Sentence for ext in special_characters):
|
||
|
|
trans_text = translation_with_spcecial_dots(
|
||
|
|
Sentence, source_lang, target_lang
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
if Sentence != Sentences[-1]:
|
||
|
|
trans_text = all_translator(Sentence, source_lang, target_lang) + i
|
||
|
|
else:
|
||
|
|
trans_text = all_translator(Sentence, source_lang, target_lang)
|
||
|
|
|
||
|
|
translated_text.append(trans_text)
|
||
|
|
|
||
|
|
return " ".join(translated_text)
|
||
|
|
|
||
|
|
|
||
|
|
def translate_comparison(text, source_lang, target_lang):
|
||
|
|
sentences = sent_tokenize(text)
|
||
|
|
special_characters = ["...", "…", ". . ."]
|
||
|
|
translated_text = []
|
||
|
|
|
||
|
|
for sentence in sentences:
|
||
|
|
if sentence == " " or sentence == "":
|
||
|
|
continue
|
||
|
|
if any(ext in sentence for ext in special_characters):
|
||
|
|
trans_text = translation_with_spcecial_dots(
|
||
|
|
sentence, source_lang, target_lang
|
||
|
|
)
|
||
|
|
translated_text.append(trans_text)
|
||
|
|
else:
|
||
|
|
trans_text = all_translator(sentence, source_lang, target_lang)
|
||
|
|
translated_text.append(trans_text)
|
||
|
|
|
||
|
|
return " ".join(translated_text)
|
||
|
|
|
||
|
|
|
||
|
|
# take a sentence and give translated sentence by comparing outputs from different resources
|
||
|
|
def compare_outputs(sentence, t0, trans, sources_name):
|
||
|
|
k = []
|
||
|
|
s = []
|
||
|
|
methods_name = {
|
||
|
|
"0": "MNF",
|
||
|
|
"1": "Gleu",
|
||
|
|
"2": "Meteor",
|
||
|
|
"3": "Rougen",
|
||
|
|
"4": "Rougel",
|
||
|
|
}
|
||
|
|
google_output = t0
|
||
|
|
# print("google", google_output)
|
||
|
|
output1, source1 = manual_diff_score(trans, sources_name)
|
||
|
|
# print("MNF", output1)
|
||
|
|
output2, source2 = gleu_diff_score(trans, sources_name)
|
||
|
|
# print("gleu", output2)
|
||
|
|
output3, source3 = meteor_diff_score(trans, sources_name)
|
||
|
|
# print("meteor", output3)
|
||
|
|
output4, source4, output5, source5 = rouge_diff_score(trans, sources_name)
|
||
|
|
# print("rougen", output4)
|
||
|
|
# print("rougel", output5)
|
||
|
|
|
||
|
|
if google_output == output1 == output2 == output3 == output4 == output5:
|
||
|
|
# print("all output is same as google")
|
||
|
|
return google_output
|
||
|
|
else:
|
||
|
|
if google_output != output1:
|
||
|
|
k.append(output1)
|
||
|
|
s.append(source1)
|
||
|
|
else:
|
||
|
|
k.append(" ")
|
||
|
|
s.append(" ")
|
||
|
|
if google_output != output2:
|
||
|
|
k.append(output2)
|
||
|
|
s.append(source2)
|
||
|
|
else:
|
||
|
|
k.append(" ")
|
||
|
|
s.append(" ")
|
||
|
|
if google_output != output3:
|
||
|
|
k.append(output3)
|
||
|
|
s.append(source3)
|
||
|
|
else:
|
||
|
|
k.append(" ")
|
||
|
|
s.append(" ")
|
||
|
|
if google_output != output4:
|
||
|
|
k.append(output4)
|
||
|
|
s.append(source4)
|
||
|
|
else:
|
||
|
|
k.append(" ")
|
||
|
|
s.append(" ")
|
||
|
|
if google_output != output5:
|
||
|
|
k.append(output5)
|
||
|
|
s.append(source5)
|
||
|
|
else:
|
||
|
|
k.append(" ")
|
||
|
|
s.append(" ")
|
||
|
|
|
||
|
|
k.insert(0, sentence)
|
||
|
|
k.insert(1, google_output)
|
||
|
|
s1ANDm1, s2ANDm2, s3ANDm3 = selection_source(
|
||
|
|
s, sources_name, trans, methods_name
|
||
|
|
)
|
||
|
|
# print("s1", s1ANDm1)
|
||
|
|
# print("s2", s2ANDm2)
|
||
|
|
# print("s3", s3ANDm3)
|
||
|
|
# print(s1ANDm1[0])
|
||
|
|
# print(sources_name)
|
||
|
|
|
||
|
|
# add_dial_comparison_doc1a(doc1a, table1a , k, s, s1ANDm1[0])
|
||
|
|
# add_dial_comparison_doc1b(doc1b, table1b , k, s, s1ANDm1[0])
|
||
|
|
add_dial_comparison_doc2(
|
||
|
|
doc2, table2, sentence, s1ANDm1, s2ANDm2, s3ANDm3, sources_name, trans
|
||
|
|
)
|
||
|
|
|
||
|
|
for a, b in sources_name.items():
|
||
|
|
if b == s1ANDm1[0]:
|
||
|
|
k = a
|
||
|
|
output1 = trans[str(k)]
|
||
|
|
return output1
|
||
|
|
|
||
|
|
|
||
|
|
def add_dial_comparison_doc1a(doc1a, table1a, k, s, selected_source):
|
||
|
|
row_Cells = table1a.add_row().cells
|
||
|
|
for i in range(4):
|
||
|
|
row_Cells[i].text = k[i]
|
||
|
|
for i in range(2):
|
||
|
|
if s[i] != " ":
|
||
|
|
if s[i] == selected_source:
|
||
|
|
row_Cells[i + 2].paragraphs[0].add_run(
|
||
|
|
"(Source : " + s[i] + ")"
|
||
|
|
).bold = True
|
||
|
|
else:
|
||
|
|
row_Cells[i + 2].paragraphs[0].add_run("(Source : " + s[i] + ")")
|
||
|
|
|
||
|
|
|
||
|
|
def add_dial_comparison_doc1b(doc1b, table1b, k, s, selected_source):
|
||
|
|
row_Cells = table1b.add_row().cells
|
||
|
|
n = len(k)
|
||
|
|
for i in range(4, n):
|
||
|
|
row_Cells[i - 4].text = k[i]
|
||
|
|
|
||
|
|
for i in range(4):
|
||
|
|
if s[i + 2] != " ":
|
||
|
|
if s[i + 2] == selected_source:
|
||
|
|
row_Cells[i].paragraphs[0].add_run(
|
||
|
|
"(Source : " + s[i + 2] + ")"
|
||
|
|
).bold = True
|
||
|
|
else:
|
||
|
|
row_Cells[i].paragraphs[0].add_run("(Source : " + s[i + 2] + ")")
|
||
|
|
|
||
|
|
|
||
|
|
# to return the table with best 3 outputs
|
||
|
|
def add_dial_comparison_doc2(
|
||
|
|
doc2, table2, sentence, s1ANDm1, s2ANDm2, s3ANDm3, sources_name, trans
|
||
|
|
):
|
||
|
|
row_Cells = table2.add_row().cells
|
||
|
|
for a, b in sources_name.items():
|
||
|
|
# print(sources_name.items())
|
||
|
|
# print(b)
|
||
|
|
# print(s1ANDm1[0])
|
||
|
|
|
||
|
|
if b == s1ANDm1[0]:
|
||
|
|
k = a
|
||
|
|
output1 = trans[str(k)]
|
||
|
|
|
||
|
|
row_Cells[0].text = sentence
|
||
|
|
row_Cells[1].text = output1
|
||
|
|
row_Cells[1].paragraphs[0].add_run("(Source : " + str(s1ANDm1[0]) + ")")
|
||
|
|
row_Cells[1].paragraphs[0].add_run("(Methods : " + str(s1ANDm1[1]) + ")")
|
||
|
|
|
||
|
|
if s2ANDm2[0] == "":
|
||
|
|
row_Cells[2].text = ""
|
||
|
|
else:
|
||
|
|
for a, b in sources_name.items():
|
||
|
|
if b == s2ANDm2[0]:
|
||
|
|
k = a
|
||
|
|
output2 = trans[str(k)]
|
||
|
|
row_Cells[2].text = output2
|
||
|
|
row_Cells[2].paragraphs[0].add_run("(Source : " + str(s2ANDm2[0]) + ")")
|
||
|
|
row_Cells[2].paragraphs[0].add_run("(Methods : " + str(s2ANDm2[1]) + ")")
|
||
|
|
|
||
|
|
if s3ANDm3[0] == "":
|
||
|
|
row_Cells[3].text = ""
|
||
|
|
else:
|
||
|
|
for a, b in sources_name.items():
|
||
|
|
if b == s3ANDm3[0]:
|
||
|
|
k = a
|
||
|
|
output3 = trans[str(k)]
|
||
|
|
row_Cells[3].text = output3
|
||
|
|
row_Cells[3].paragraphs[0].add_run("(Source : " + str(s3ANDm3[0]) + ")")
|
||
|
|
row_Cells[3].paragraphs[0].add_run("(Methods : " + str(s3ANDm3[1]) + ")")
|
||
|
|
|
||
|
|
|
||
|
|
for scene in tqdm(scenes[:5]):
|
||
|
|
for i, line in enumerate(scene):
|
||
|
|
if i == 0:
|
||
|
|
addSlugLine(doc, line)
|
||
|
|
continue
|
||
|
|
if type(line) == type(""):
|
||
|
|
|
||
|
|
if global_non_dialogue_flag == "Yes":
|
||
|
|
|
||
|
|
# non_dial_src_lang = language_detector(line)
|
||
|
|
# non_dial_translate = non_dial_checker( non_dial_dest_lang, non_dial_src_lang )
|
||
|
|
# print("non_dial_translate", non_dial_translate)
|
||
|
|
# if non_dial_translate:
|
||
|
|
# if non_dial_src_lang in translation_list and non_dial_dest_lang in translation_list:
|
||
|
|
# trans_text = translate_comparison(line , non_dial_src_lang, non_dial_dest_lang)
|
||
|
|
# addActionLine(doc, trans_text, non_dial_dest_lang)
|
||
|
|
# else:
|
||
|
|
# addActionLine(doc, line, non_dial_dest_lang)
|
||
|
|
|
||
|
|
if (
|
||
|
|
non_dial_src_lang in translation_list
|
||
|
|
and non_dial_dest_lang in translation_list
|
||
|
|
):
|
||
|
|
trans_text = translate_comparison(
|
||
|
|
line, non_dial_src_lang, non_dial_dest_lang
|
||
|
|
)
|
||
|
|
addActionLine(doc, trans_text, non_dial_dest_lang)
|
||
|
|
else:
|
||
|
|
addActionLine(doc, line, non_dial_dest_lang)
|
||
|
|
|
||
|
|
else:
|
||
|
|
addActionLine(doc, line, non_dial_dest_lang)
|
||
|
|
|
||
|
|
else:
|
||
|
|
# print(line)
|
||
|
|
[speaker] = line.keys()
|
||
|
|
# print([speaker])
|
||
|
|
if speaker == "Transition":
|
||
|
|
addTransition(doc, line[speaker])
|
||
|
|
continue
|
||
|
|
addSpeaker(doc, speaker)
|
||
|
|
|
||
|
|
if global_dialogue_flag == "Yes":
|
||
|
|
print("In dialogue")
|
||
|
|
|
||
|
|
dial_src_lang = language_detector(line[speaker][2])
|
||
|
|
print("dial_src_lang", dial_src_lang)
|
||
|
|
|
||
|
|
# print("p", line[speaker][0])
|
||
|
|
if line[speaker][0] != "NONE":
|
||
|
|
out = google(line[speaker][0], dial_src_lang, dial_dest_lang)
|
||
|
|
addParenthetical(doc, out)
|
||
|
|
# else:
|
||
|
|
# addParenthetical(doc,line[speaker][0])
|
||
|
|
|
||
|
|
dial_translate = dial_checker(dial_dest_lang, dial_src_lang)
|
||
|
|
print("dial_translate", dial_translate)
|
||
|
|
|
||
|
|
if dial_translate:
|
||
|
|
print("dialogue to be translated", line[speaker][2])
|
||
|
|
if line[speaker][2] == "":
|
||
|
|
continue
|
||
|
|
|
||
|
|
if (
|
||
|
|
dial_src_lang in translation_list
|
||
|
|
and dial_dest_lang in translation_list
|
||
|
|
):
|
||
|
|
trans_text = translate_comparison(
|
||
|
|
line[speaker][2], dial_src_lang, dial_dest_lang
|
||
|
|
)
|
||
|
|
|
||
|
|
if dual_dial_script == "Yes":
|
||
|
|
dual_script(doc, line[speaker][2], trans_text, dial_dest_lang)
|
||
|
|
else:
|
||
|
|
addDialogue(doc, trans_text, dial_dest_lang)
|
||
|
|
|
||
|
|
else:
|
||
|
|
addDialogue(doc, line[speaker][2], dial_dest_lang)
|
||
|
|
else:
|
||
|
|
addParenthetical(doc, line[speaker][0])
|
||
|
|
addDialogue(doc, line[speaker][2], dial_dest_lang)
|
||
|
|
|
||
|
|
doc.save(doc_file)
|
||
|
|
# doc1a.save("1"+doc_file)
|
||
|
|
# doc1b.save("2"+doc_file)
|
||
|
|
doc2.save(
|
||
|
|
str(filename1.split(".")[0])
|
||
|
|
+ "_trans_to_"
|
||
|
|
+ str(dial_dest_lang)
|
||
|
|
+ "_"
|
||
|
|
+ "final.docx"
|
||
|
|
)
|