| |
|
|
| import re |
| import torch |
| import numpy as np |
| import subprocess |
| import os |
|
|
| def split_num(num): |
| num = num.group() |
| if '.' in num: |
| return num |
| elif ':' in num: |
| h, m = [int(n) for n in num.split(':')] |
| if m == 0: |
| return f"{h} o'clock" |
| elif m < 10: |
| return f'{h} oh {m}' |
| return f'{h} {m}' |
| year = int(num[:4]) |
| if year < 1100 or year % 1000 < 10: |
| return num |
| left, right = num[:2], int(num[2:4]) |
| s = 's' if num.endswith('s') else '' |
| if 100 <= year % 1000 <= 999: |
| if right == 0: |
| return f'{left} hundred{s}' |
| elif right < 10: |
| return f'{left} oh {right}{s}' |
| return f'{left} {right}{s}' |
|
|
| def flip_money(m): |
| m = m.group() |
| bill = 'dollar' if m[0] == '$' else 'pound' |
| if m[-1].isalpha(): |
| return f'{m[1:]} {bill}s' |
| elif '.' not in m: |
| s = '' if m[1:] == '1' else 's' |
| return f'{m[1:]} {bill}{s}' |
| b, c = m[1:].split('.') |
| s = '' if b == '1' else 's' |
| c = int(c.ljust(2, '0')) |
| coins = f"cent{'' if c == 1 else 's'}" if m[0] == '$' else ('penny' if c == 1 else 'pence') |
| return f'{b} {bill}{s} and {c} {coins}' |
|
|
| def point_num(num): |
| a, b = num.group().split('.') |
| return ' point '.join([a, ' '.join(b)]) |
|
|
| def expand_acronym(m): |
| text = m.group(0).replace('.', '') |
| letters = list(text) |
| letters_with_periods = [letter + '.' for letter in letters] |
| return ' '.join(letters_with_periods) |
|
|
| def normalize_text(text): |
| text = text.replace(chr(8216), "'").replace(chr(8217), "'") |
| text = text.replace('«', chr(8220)).replace('»', chr(8221)) |
| text = text.replace(chr(8220), '"').replace(chr(8221), '"') |
| text = text.replace('(', '«').replace(')', '»') |
| for a, b in zip('、。！，：；？', ',.!,:;?'): |
| text = text.replace(a, b+' ') |
| text = re.sub(r'[^\S \n]', ' ', text) |
| text = re.sub(r' +', ' ', text) |
| text = re.sub(r'(?<=\n) +(?=\n)', '', text) |
| text = re.sub(r'\bD[Rr]\.(?= [A-Z])', 'Doctor', text) |
| text = re.sub(r'\b(?:Mr\.|MR\.(?= [A-Z]))', 'Mister', text) |
| text = re.sub(r'\b(?:Ms\.|MS\.(?= [A-Z]))', 'Miss', text) |
| text = re.sub(r'\b(?:Mrs\.|MRS\.(?= [A-Z]))', 'Mrs', text) |
| text = re.sub(r'\betc\.(?! [A-Z])', 'etc', text) |
| text = re.sub(r'(?i)\b(y)eah?\b', r"\1e'a", text) |
| text = re.sub(r'\d*\.\d+|\b\d{4}s?\b|(?<!:)\b(?:[1-9]|1[0-2]):[0-5]\d\b(?!:)', split_num, text) |
| text = re.sub(r'(?<=\d),(?=\d)', '', text) |
| text = re.sub(r'(?i)[$£]\d+(?:\.\d+)?(?: hundred| thousand| (?:[bm]|tr)illion)*\b|[$£]\d+\.\d\d?\b', flip_money, text) |
| text = re.sub(r'\d*\.\d+', point_num, text) |
| text = re.sub(r'(?<=\d)-(?=\d)', ' to ', text) |
| text = re.sub(r'(?<=\d)S', ' S', text) |
| text = re.sub(r"(?<=[BCDFGHJ-NP-TV-Z])'?s\b", "'S", text) |
| text = re.sub(r"(?<=X')S\b", 's', text) |
| text = re.sub(r'(?:[A-Za-z]\.){2,} [a-z]', lambda m: m.group().replace('.', '-'), text) |
| text = re.sub(r'(?i)(?<=[A-Z])\.(?=[A-Z])', '-', text) |
| text = re.sub(r'\b(?:[A-Z]\.?){2,}\b', expand_acronym, text) |
| return text.strip() |
|
|
| def get_vocab(): |
| _pad = "$" |
| _punctuation = ';:,.!?¡¿—…"«»"" ' |
| _letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz' |
| _letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ" |
| symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa) |
| dicts = {} |
| for i in range(len((symbols))): |
| dicts[symbols[i]] = i |
| return dicts |
|
|
| VOCAB = get_vocab() |
|
|
| def tokenize(ps): |
| return [i for i in map(VOCAB.get, ps) if i is not None] |
|
|
| def direct_espeak(text, lang='en-us'): |
| espeak_path = os.path.join(os.path.dirname(__file__), 'espeak-ng.exe') |
| cmd = [espeak_path, '-q', '--ipa', '-v', lang, text] |
| try: |
| result = subprocess.run( |
| cmd, |
| capture_output=True, |
| text=True, |
| encoding='utf-8', |
| shell=True |
| ) |
| if result.returncode != 0: |
| print(f"Espeak error: {result.stderr}") |
| return '' |
| return result.stdout.strip() |
| except Exception as e: |
| print(f"Error running espeak: {e}") |
| return '' |
|
|
| def phonemize(text, lang, norm=True): |
| if norm: |
| text = normalize_text(text) |
| |
| espeak_lang = 'en-us' if lang == 'a' else 'en-gb' |
| ps = direct_espeak(text, espeak_lang) |
| if not ps: |
| return '' |
| |
| ps = ps.replace('ʲ', 'j').replace('r', 'ɹ').replace('x', 'k').replace('ɬ', 'l') |
| ps = re.sub(r'(?<=[a-zɹː])(?=hˈʌndɹɪd)', ' ', ps) |
| ps = re.sub(r' z(?=[;:,.!?¡¿—…"«»"" ]|$)', 'z', ps) |
| if lang == 'a': |
| ps = re.sub(r'(?<=nˈaɪn)ti(?!ː)', 'di', ps) |
| ps = ''.join(filter(lambda p: p in VOCAB, ps)) |
| return ps.strip() |
|
|
| def length_to_mask(lengths): |
| mask = torch.arange(lengths.max()).unsqueeze(0).expand(lengths.shape[0], -1).type_as(lengths) |
| mask = torch.gt(mask+1, lengths.unsqueeze(1)) |
| return mask |
|
|
| @torch.no_grad() |
| def forward(model, tokens, ref_s, speed): |
| device = ref_s.device |
| tokens = torch.LongTensor([[0, *tokens, 0]]).to(device) |
| input_lengths = torch.LongTensor([tokens.shape[-1]]).to(device) |
| text_mask = length_to_mask(input_lengths).to(device) |
| bert_dur = model.bert(tokens, attention_mask=(~text_mask).int()) |
| d_en = model.bert_encoder(bert_dur).transpose(-1, -2) |
| s = ref_s[:, 128:] |
| d = model.predictor.text_encoder(d_en, s, input_lengths, text_mask) |
| x, _ = model.predictor.lstm(d) |
| duration = model.predictor.duration_proj(x) |
| duration = torch.sigmoid(duration).sum(axis=-1) / speed |
| pred_dur = torch.round(duration).clamp(min=1).long() |
| pred_aln_trg = torch.zeros(input_lengths, pred_dur.sum().item()) |
| c_frame = 0 |
| for i in range(pred_aln_trg.size(0)): |
| pred_aln_trg[i, c_frame:c_frame + pred_dur[0,i].item()] = 1 |
| c_frame += pred_dur[0,i].item() |
| en = d.transpose(-1, -2) @ pred_aln_trg.unsqueeze(0).to(device) |
| F0_pred, N_pred = model.predictor.F0Ntrain(en, s) |
| t_en = model.text_encoder(tokens, input_lengths, text_mask) |
| asr = t_en @ pred_aln_trg.unsqueeze(0).to(device) |
| return model.decoder(asr, F0_pred, N_pred, ref_s[:, :128]).squeeze().cpu().numpy() |
|
|
| def generate(model, text, voicepack, lang='a', speed=1, ps=None): |
| ps = ps or phonemize(text, lang) |
| tokens = tokenize(ps) |
| if not tokens: |
| return None |
| elif len(tokens) > 510: |
| tokens = tokens[:510] |
| print('Truncated to 510 tokens') |
| ref_s = voicepack[len(tokens)] |
| out = forward(model, tokens, ref_s, speed) |
| ps = ''.join(next(k for k, v in VOCAB.items() if i == v) for i in tokens) |
| return out, ps |
|
|
| def generate_full(model, text, voicepack, lang='a', speed=1, ps=None): |
| ps = ps or phonemize(text, lang) |
| tokens = tokenize(ps) |
| if not tokens: |
| return None |
| outs = [] |
| loop_count = len(tokens)//510 + (1 if len(tokens) % 510 != 0 else 0) |
| for i in range(loop_count): |
| ref_s = voicepack[len(tokens[i*510:(i+1)*510])] |
| out = forward(model, tokens[i*510:(i+1)*510], ref_s, speed) |
| outs.append(out) |
| outs = np.concatenate(outs) |
| ps = ''.join(next(k for k, v in VOCAB.items() if i == v) for i in tokens) |
| return outs, ps |
|
|
| """ |
| THE ORIGINAL SCRIPT relied on "phonemizer" a wrapper around espeak-ng |
| |
| ```python |
| phonemizers = dict( |
| a=phonemizer.backend.EspeakBackend(language='en-us', preserve_punctuation=True, with_stress=True), |
| b=phonemizer.backend.EspeakBackend(language='en-gb', preserve_punctuation=True, with_stress=True), |
| ) |
| ``` |
| - language selection (en-us or en-gb) |
| - preserve_punctuation=True (keep punctuation in output) |
| - with_stress=True (keep stress markers in phonemes) |
| |
| This modified script uses espeak-ng directly, providing the appropriate flags for identical functionality: |
| ```python |
| def direct_espeak(text, lang='en-us'): |
| espeak_path = r"C:\Program Files\eSpeak NG\espeak-ng.exe" |
| cmd = [espeak_path, '-q', '--ipa', '-v', lang, text] |
| result = subprocess.run(cmd, capture_output=True, text=True, encoding='utf-8', shell=True) |
| ``` |
| |
| - `-q`: Quiet mode (no audio output) |
| - `--ipa`: Output in International Phonetic Alphabet notation |
| - `-v lang`: Language selection (en-us or en-gb) |
| |
| THE ORIGINAL SCRIPT set certain variables: |
| ```python |
| os.environ["PHONEMIZER_ESPEAK_LIBRARY"] = r"C:\Program Files\eSpeak NG\libespeak-ng.dll" |
| os.environ["PHONEMIZER_ESPEAK_PATH"] = r"C:\Program Files\eSpeak NG\espeak-ng.exe" |
| ``` |
| |
| - PHONEMIZER_ESPEAK_LIBRARY pointed to the DLL file that phonemizer used to interface with espeak |
| - PHONEMIZER_ESPEAK_PATH pointed to the espeak executable that phonemizer would call |
| |
| This modified script does not because we are no longer using the phonemize library, which requires |
| 1. This script specifically sets the path to the espeak binary. |
| 2. When distribution it'll be necessary to either bundle the binary and copy it to the same directory in which kokoro.py is located |
| (in which case amending the PATH is not necessary) or add functionality to search for and locate espeak. |
| |
| espeak-ng requires three files to function: |
| espeak-ng-data -- all the languages and stuff |
| espeak-ng.exe - binary that links to the .dll |
| libespeak-ng.dll |
| """ |
|
|
