File size: 6,199 Bytes
19dc0f3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
import re

from num2words import num2words

punctuation = r'[\s,.?!/)\'\]>]'
alphabet_map = {
    "A": " Ei ",
    "B": " Bee ",
    "C": " See ",
    "D": " Dee ",
    "E": " Eee ",
    "F": " Eff ",
    "G": " Jee ",
    "H": " Eich ",
    "I": " Eye ",
    "J": " Jay ",
    "K": " Kay ",
    "L": " El ",
    "M": " Emm ",
    "N": " Enn ",
    "O": " Ohh ",
    "P": " Pee ",
    "Q": " Queue ",
    "R": " Are ",
    "S": " Ess ",
    "T": " Tee ",
    "U": " You ",
    "V": " Vee ",
    "W": " Double You ",
    "X": " Ex ",
    "Y": " Why ",
    "Z": " Zed "  # Zed is weird, as I (da3dsoul) am American, but most of the voice models sound British, so it matches
}


def preprocess(string):
    # the order for some of these matter
    # For example, you need to remove the commas in numbers before expanding them
    string = remove_surrounded_chars(string)
    string = string.replace('"', '')
    string = string.replace('\u201D', '').replace('\u201C', '')  # right and left quote
    string = string.replace('\u201F', '')  # italic looking quote
    string = string.replace('\n', ' ')
    string = convert_num_locale(string)
    string = replace_negative(string)
    string = replace_roman(string)
    string = hyphen_range_to(string)
    string = num_to_words(string)

    # TODO Try to use a ML predictor to expand abbreviations. It's hard, dependent on context, and whether to actually
    # try to say the abbreviation or spell it out as I've done below is not agreed upon

    # For now, expand abbreviations to pronunciations
    # replace_abbreviations adds a lot of unnecessary whitespace to ensure separation
    string = replace_abbreviations(string)
    string = replace_lowercase_abbreviations(string)

    # cleanup whitespaces
    # remove whitespace before punctuation
    string = re.sub(rf'\s+({punctuation})', r'\1', string)
    string = string.strip()
    # compact whitespace
    string = ' '.join(string.split())

    return string


def remove_surrounded_chars(string):
    # first this expression will check if there is a string nested exclusively between a alt=
    # and a style= string. This would correspond to only a the alt text of an embedded image
    # If it matches it will only keep that part as the string, and rend it for further processing
    # Afterwards this expression matches to 'as few symbols as possible (0 upwards) between any
    # asterisks' OR' as few symbols as possible (0 upwards) between an asterisk and the end of the string'
    if re.search(r'(?<=alt=)(.*)(?=style=)', string, re.DOTALL):
        m = re.search(r'(?<=alt=)(.*)(?=style=)', string, re.DOTALL)
        string = m.group(0)
    return re.sub(r'\*[^*]*?(\*|$)', '', string)


def convert_num_locale(text):
    # This detects locale and converts it to American without comma separators
    pattern = re.compile(r'(?:\s|^)\d{1,3}(?:\.\d{3})+(,\d+)(?:\s|$)')
    result = text
    while True:
        match = pattern.search(result)
        if match is None:
            break

        start = match.start()
        end = match.end()
        result = result[0:start] + result[start:end].replace('.', '').replace(',', '.') + result[end:len(result)]

    # removes comma separators from existing American numbers
    pattern = re.compile(r'(\d),(\d)')
    result = pattern.sub(r'\1\2', result)

    return result


def replace_negative(string):
    # handles situations like -5. -5 would become negative 5, which would then be expanded to negative five
    return re.sub(rf'(\s)(-)(\d+)({punctuation})', r'\1negative \3\4', string)


def replace_roman(string):
    # find a string of roman numerals.
    # Only 2 or more, to avoid capturing I and single character abbreviations, like names
    pattern = re.compile(rf'\s[IVXLCDM]{{2,}}{punctuation}')
    result = string
    while True:
        match = pattern.search(result)
        if match is None:
            break

        start = match.start()
        end = match.end()
        result = result[0:start + 1] + str(roman_to_int(result[start + 1:end - 1])) + result[end - 1:len(result)]

    return result


def roman_to_int(s):
    rom_val = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
    int_val = 0
    for i in range(len(s)):
        if i > 0 and rom_val[s[i]] > rom_val[s[i - 1]]:
            int_val += rom_val[s[i]] - 2 * rom_val[s[i - 1]]
        else:
            int_val += rom_val[s[i]]
    return int_val


def hyphen_range_to(text):
    pattern = re.compile(r'(\d+)[-–](\d+)')
    result = pattern.sub(lambda x: x.group(1) + ' to ' + x.group(2), text)
    return result


def num_to_words(text):
    # 1000 or 10.23
    pattern = re.compile(r'\d+\.\d+|\d+')
    result = pattern.sub(lambda x: num2words(float(x.group())), text)
    return result


def replace_abbreviations(string):
    # abbreviations 1 to 4 characters long. It will get things like A and I, but those are pronounced with their letter
    pattern = re.compile(rf'(^|[\s(.\'\[<])([A-Z]{{1,4}})({punctuation}|$)')
    result = string
    while True:
        match = pattern.search(result)
        if match is None:
            break

        start = match.start()
        end = match.end()
        result = result[0:start] + replace_abbreviation(result[start:end]) + result[end:len(result)]

    return result


def replace_lowercase_abbreviations(string):
    # abbreviations 1 to 4 characters long, separated by dots i.e. e.g.
    pattern = re.compile(rf'(^|[\s(.\'\[<])(([a-z]\.){{1,4}})({punctuation}|$)')
    result = string
    while True:
        match = pattern.search(result)
        if match is None:
            break

        start = match.start()
        end = match.end()
        result = result[0:start] + replace_abbreviation(result[start:end].upper()) + result[end:len(result)]

    return result


def replace_abbreviation(string):
    result = ""
    for char in string:
        result += match_mapping(char)

    return result


def match_mapping(char):
    for mapping in alphabet_map.keys():
        if char == mapping:
            return alphabet_map[char]

    return char


def __main__(args):
    print(preprocess(args[1]))


if __name__ == "__main__":
    import sys
    __main__(sys.argv)