""" from https://github.com/keithito/tacotron """ import numpy as np import re from . import cleaners from .symbols import symbols # Mappings from symbol to numeric ID and vice versa: _symbol_to_id = {s: i for i, s in enumerate(symbols)} _id_to_symbol = {i: s for i, s in enumerate(symbols)} # Regular expression matching text enclosed in curly braces: _curly_re = re.compile(r'(.*?)\{(.+?)\}(.*)') # Special symbols SOS_TOK = '' EOS_TOK = '' def text_to_sequence(text, cleaner_names): '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text. The text can optionally have ARPAbet sequences enclosed in curly braces embedded in it. For example, "Turn left on {HH AW1 S S T AH0 N} Street." Args: text: string to convert to a sequence cleaner_names: names of the cleaner functions to run the text through Returns: List of integers corresponding to the symbols in the text ''' sequence = [] # Check for curly braces and treat their contents as ARPAbet: while len(text): m = _curly_re.match(text) if not m: sequence += _symbols_to_sequence(_clean_text(text, cleaner_names)) break sequence += _symbols_to_sequence(_clean_text(m.group(1), cleaner_names)) sequence += _arpabet_to_sequence(m.group(2)) text = m.group(3) return sequence def sample_code_chunk(code, size): assert(size > 0 and size <= len(code)) start = np.random.randint(len(code) - size + 1) end = start + size return code[start:end], start, end def code_to_sequence(code, code_dict, collapse_code): if collapse_code: prev_c = None sequence = [] for c in code: if c in code_dict and c != prev_c: sequence.append(code_dict[c]) prev_c = c else: sequence = [code_dict[c] for c in code if c in code_dict] if len(sequence) < 0.95 * len(code): print('WARNING : over 5%% codes are OOV') return sequence def sequence_to_text(sequence): '''Converts a sequence of IDs back to a string''' result = '' for symbol_id in sequence: if symbol_id in _id_to_symbol: s = _id_to_symbol[symbol_id] # Enclose ARPAbet back in curly braces: if len(s) > 1 and s[0] == '@': s = '{%s}' % s[1:] result += s return result.replace('}{', ' ') def sequence_to_code(sequence, code_dict): '''Analogous to sequence_to_text''' id_to_code = {i: c for c, i in code_dict.items()} return ' '.join([id_to_code[i] for i in sequence]) def _clean_text(text, cleaner_names): for name in cleaner_names: cleaner = getattr(cleaners, name) if not cleaner: raise Exception('Unknown cleaner: %s' % name) text = cleaner(text) return text def _symbols_to_sequence(symbols): return [_symbol_to_id[s] for s in symbols if _should_keep_symbol(s)] def _arpabet_to_sequence(text): return _symbols_to_sequence(['@' + s for s in text.split()]) def _should_keep_symbol(s): return s in _symbol_to_id and s != '_' and s != '~'