Spaces:
Sleeping
Sleeping
Upload app.py
Browse files
app.py
CHANGED
|
@@ -180,6 +180,22 @@ def resolve_voices(voice, warn=True):
|
|
| 180 |
voices = [v for v in voices if v in VOICES['cpu']]
|
| 181 |
return voices if voices else ['af']
|
| 182 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 183 |
def phonemize(text, voice, norm=True):
|
| 184 |
lang = resolve_voices(voice)[0][0]
|
| 185 |
if norm:
|
|
@@ -212,22 +228,6 @@ def length_to_mask(lengths):
|
|
| 212 |
mask = torch.gt(mask+1, lengths.unsqueeze(1))
|
| 213 |
return mask
|
| 214 |
|
| 215 |
-
def get_vocab():
|
| 216 |
-
_pad = "$"
|
| 217 |
-
_punctuation = ';:,.!?¡¿—…"«»“” '
|
| 218 |
-
_letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
|
| 219 |
-
_letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
|
| 220 |
-
symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa)
|
| 221 |
-
dicts = {}
|
| 222 |
-
for i in range(len((symbols))):
|
| 223 |
-
dicts[symbols[i]] = i
|
| 224 |
-
return dicts
|
| 225 |
-
|
| 226 |
-
VOCAB = get_vocab()
|
| 227 |
-
|
| 228 |
-
def tokenize(ps):
|
| 229 |
-
return [i for i in map(VOCAB.get, ps) if i is not None]
|
| 230 |
-
|
| 231 |
SAMPLE_RATE = 24000
|
| 232 |
|
| 233 |
@torch.no_grad()
|
|
|
|
| 180 |
voices = [v for v in voices if v in VOICES['cpu']]
|
| 181 |
return voices if voices else ['af']
|
| 182 |
|
| 183 |
+
def get_vocab():
|
| 184 |
+
_pad = "$"
|
| 185 |
+
_punctuation = ';:,.!?¡¿—…"«»“” '
|
| 186 |
+
_letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
|
| 187 |
+
_letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
|
| 188 |
+
symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa)
|
| 189 |
+
dicts = {}
|
| 190 |
+
for i in range(len((symbols))):
|
| 191 |
+
dicts[symbols[i]] = i
|
| 192 |
+
return dicts
|
| 193 |
+
|
| 194 |
+
VOCAB = get_vocab()
|
| 195 |
+
|
| 196 |
+
def tokenize(ps):
|
| 197 |
+
return [i for i in map(VOCAB.get, ps) if i is not None]
|
| 198 |
+
|
| 199 |
def phonemize(text, voice, norm=True):
|
| 200 |
lang = resolve_voices(voice)[0][0]
|
| 201 |
if norm:
|
|
|
|
| 228 |
mask = torch.gt(mask+1, lengths.unsqueeze(1))
|
| 229 |
return mask
|
| 230 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 231 |
SAMPLE_RATE = 24000
|
| 232 |
|
| 233 |
@torch.no_grad()
|