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Merge pull request #840 from ROBERT-MCDOWELL/v25

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v25.6.16
This commit is contained in:
ROBERT MCDOWELL
2025-06-15 19:30:22 -07:00
committed by GitHub
parent 6f8cbf4166 4f8e96b7b6
commit d8e86a3bad
11 changed files with 190 additions and 173 deletions
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4
README.md
View File

@@ -331,13 +331,13 @@ Linux/Mac:
Headless mode:
./ebook2audiobook.sh --headless --ebook '/path/to/file'
Tip: to add of silence (2 seconds) into your text just use "###" or "[pause]".
Tip: to add of silence (1.4 seconds) into your text just use "###" or "[pause]".
```
NOTE: in gradio/gui mode, to cancel a running conversion, just click on the [X] from the ebook upload component.
TIP: if it needs some more pauses, just add '###' or '[pause]' between the words you wish more pause. one [pause] equals to 2 seconds
TIP: if it needs some more pauses, just add '###' or '[pause]' between the words you wish more pause. one [pause] equals to 1.4 seconds
#### Docker GPU Options

2
VERSION.txt
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@@ -1 +1 @@
25.6.14
25.6.16

5
ebook2audiobook.egg-info/requires.txt
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@@ -10,10 +10,10 @@ gradio
hangul-romanize
indic-nlp-library
iso-639
jieba
jieba
mecab
mecab-python3
konlpy
soynlp
pythainlp
m4b-util
nvidia-ml-py
@@ -24,7 +24,6 @@ ray
regex
translate
tqdm
suno-bark
unidic
pymupdf4llm
sudachipy

41
ebook2audiobook.sh
View File

@@ -48,7 +48,8 @@ SCRIPT_MODE="$NATIVE"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
WGET=$(which wget 2>/dev/null)
REQUIRED_PROGRAMS=("calibre" "ffmpeg" "nodejs" "mecab" "espeak-ng" "rust" "sox")
#REQUIRED_PROGRAMS=("calibre" "ffmpeg" "nodejs" "mecab" "espeak-ng" "rust" "sox")
REQUIRED_PROGRAMS=("calibre" "ffmpeg" "nodejs" "espeak-ng" "rust" "sox")
PYTHON_ENV="python_env"
CURRENT_ENV=""
@@ -159,37 +160,37 @@ else
echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> $HOME/.zprofile
eval "$(/opt/homebrew/bin/brew shellenv)"
fi
mecab_extra="mecab-ipadic"
#mecab_extra="mecab-ipadic"
else
SUDO="sudo"
echo -e "\e[33mInstalling required programs. NOTE: you must have 'sudo' priviliges to install ebook2audiobook.\e[0m"
PACK_MGR_OPTIONS=""
if command -v emerge &> /dev/null; then
PACK_MGR="emerge"
mecab_extra="app-text/mecab app-text/mecab-ipadic"
#mecab_extra="app-text/mecab app-text/mecab-ipadic"
elif command -v dnf &> /dev/null; then
PACK_MGR="dnf install"
PACK_MGR_OPTIONS="-y"
mecab_extra="mecab-devel mecab-ipadic"
#mecab_extra="mecab-devel mecab-ipadic"
elif command -v yum &> /dev/null; then
PACK_MGR="yum install"
PACK_MGR_OPTIONS="-y"
mecab_extra="mecab-devel mecab-ipadic"
#mecab_extra="mecab-devel mecab-ipadic"
elif command -v zypper &> /dev/null; then
PACK_MGR="zypper install"
PACK_MGR_OPTIONS="-y"
mecab_extra="mecab-devel mecab-ipadic"
#mecab_extra="mecab-devel mecab-ipadic"
elif command -v pacman &> /dev/null; then
PACK_MGR="pacman -Sy"
mecab_extra="mecab-devel mecab-ipadic"
#mecab_extra="mecab-devel mecab-ipadic"
elif command -v apt-get &> /dev/null; then
$SUDO apt-get update
PACK_MGR="apt-get install"
PACK_MGR_OPTIONS="-y"
mecab_extra="libmecab-dev mecab-ipadic-utf8"
#mecab_extra="libmecab-dev mecab-ipadic-utf8"
elif command -v apk &> /dev/null; then
PACK_MGR="apk add"
mecab_extra="mecab-dev mecab-ipadic"
#mecab_extra="mecab-dev mecab-ipadic"
else
echo "Cannot recognize your applications package manager. Please install the required applications manually."
return 1
@@ -227,17 +228,17 @@ else
echo "$program installation failed."
fi
fi
elif [ "$program" = "mecab" ];then
if command -v emerge &> /dev/null; then
eval "$SUDO $PACK_MGR $mecab_extra $PACK_MGR_OPTIONS"
else
eval "$SUDO $PACK_MGR $program $mecab_extra $PACK_MGR_OPTIONS"
fi
if command -v $program >/dev/null 2>&1; then
echo -e "\e[32m===============>>> $program is installed! <<===============\e[0m"
else
echo "$program installation failed."
fi
#elif [ "$program" = "mecab" ];then
# if command -v emerge &> /dev/null; then
# eval "$SUDO $PACK_MGR $mecab_extra $PACK_MGR_OPTIONS"
# else
# eval "$SUDO $PACK_MGR $program $mecab_extra $PACK_MGR_OPTIONS"
# fi
# if command -v $program >/dev/null 2>&1; then
# echo -e "\e[32m===============>>> $program is installed! <<===============\e[0m"
# else
# echo "$program installation failed."
# fi
elif [ "$program" = "rust" ]; then
if command -v apt-get &> /dev/null; then
app="rustc"

274
lib/classes/tts_engines/coqui.py
View File

@@ -29,7 +29,6 @@ lock = threading.Lock()
xtts_builtin_speakers_list = None
def _safe_multinomial(input, num_samples, replacement=False, *, generator=None, out=None):
#with torch.no_grad():
input = torch.nan_to_num(input, nan=0.0, posinf=0.0, neginf=0.0)
input = torch.clamp(input, min=0.0)
sum_input = input.sum(dim=-1, keepdim=True)
@@ -65,10 +64,10 @@ class Coqui:
if xtts_builtin_speakers_list is None:
self.speakers_path = hf_hub_download(repo_id=models[XTTSv2]['internal']['repo'], filename=default_xtts_settings['files'][4], cache_dir=self.cache_dir)
xtts_builtin_speakers_list = torch.load(self.speakers_path)
msg = f"Loading TTS {self.session['tts_engine']} model, it takes a while, please be patient..."
print(msg)
if self.session['tts_engine'] == XTTSv2:
self.params[XTTSv2]['sample_rate'] = models[XTTSv2][self.session['fine_tuned']]['samplerate']
msg = f"Loading TTS {self.session['tts_engine']} model, it takes a while, please be patient..."
print(msg)
if self.session['custom_model'] is not None:
config_path = os.path.join(self.session['custom_model_dir'], self.session['tts_engine'], self.session['custom_model'], default_xtts_settings['files'][0])
checkpoint_path = os.path.join(self.session['custom_model_dir'], self.session['tts_engine'], self.session['custom_model'], default_xtts_settings['files'][1])
@@ -245,7 +244,7 @@ class Coqui:
config = BarkConfig()
config.CACHE_DIR = self.cache_dir
config.USE_SMALLER_MODELS = os.environ.get('SUNO_USE_SMALL_MODELS', '').lower() == 'true'
tts = Bark(config)
tts = Bark.init_from_config(config)
tts.load_checkpoint(
config,
checkpoint_dir=checkpoint_dir,
@@ -272,9 +271,9 @@ class Coqui:
try:
voice_parts = Path(voice_path).parts
if self.session['language'] not in voice_parts:
if speaker in default_xtts_settings['voices'].keys() and self.session['language'] in language_tts[XTTSv2].keys():
if self.session['language'] in language_tts[XTTSv2].keys():
lang_dir = 'con-' if self.session['language'] == 'con' else self.session['language']
voice_path = voice_path.replace('/eng/',f'/{lang_dir}/').replace('\\eng\\',f'\\{lang_dir}\\')
new_voice_path = voice_path.replace('/eng/',f'/{lang_dir}/').replace('\\eng\\',f'\\{lang_dir}\\')
default_text_file = os.path.join(voices_dir, self.session['language'], 'default.txt')
if os.path.exists(default_text_file):
msg = f"Converting builtin eng voice to {self.session['language']}..."
@@ -283,20 +282,40 @@ class Coqui:
default_text = Path(default_text_file).read_text(encoding="utf-8")
hf_repo = models[XTTSv2]['internal']['repo']
hf_sub = ''
config_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][0]}", cache_dir=self.cache_dir)
checkpoint_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][1]}", cache_dir=self.cache_dir)
vocab_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][2]}", cache_dir=self.cache_dir)
tts = self._load_checkpoint(tts_engine=XTTSv2, key=tts_internal_key, checkpoint_path=checkpoint_path, config_path=config_path, vocab_path=vocab_path, device=device)
tts = (loaded_tts.get(tts_internal_key) or {}).get('engine', False)
if not tts:
config_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][0]}", cache_dir=self.cache_dir)
checkpoint_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][1]}", cache_dir=self.cache_dir)
vocab_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[XTTSv2]['internal']['files'][2]}", cache_dir=self.cache_dir)
tts = self._load_checkpoint(tts_engine=XTTSv2, key=tts_internal_key, checkpoint_path=checkpoint_path, config_path=config_path, vocab_path=vocab_path, device=device)
if tts:
file_path = voice_path.replace('_24000.wav', '.wav').replace('/eng/', f'/{lang_dir}/').replace('\\eng\\', f'\\{lang_dir}\\')
gpt_cond_latent, speaker_embedding = xtts_builtin_speakers_list[default_xtts_settings['voices'][speaker]].values()
#with torch.no_grad():
result = tts.inference(
text=default_text,
language=self.session['language_iso1'],
gpt_cond_latent=gpt_cond_latent,
speaker_embedding=speaker_embedding,
)
file_path = new_voice_path.replace('_24000.wav', '.wav')
if speaker in default_xtts_settings['voices'].keys():
gpt_cond_latent, speaker_embedding = xtts_builtin_speakers_list[default_xtts_settings['voices'][speaker]].values()
else:
gpt_cond_latent, speaker_embedding = tts.get_conditioning_latents(audio_path=[voice_path])
fine_tuned_params = {
key: cast_type(self.session[key])
for key, cast_type in {
"temperature": float,
"length_penalty": float,
"num_beams": int,
"repetition_penalty": float,
"top_k": int,
"top_p": float,
"speed": float,
"enable_text_splitting": bool
}.items()
if self.session.get(key) is not None
}
with torch.no_grad():
result = tts.inference(
text=default_text,
language=self.session['language_iso1'],
gpt_cond_latent=gpt_cond_latent,
speaker_embedding=speaker_embedding,
**fine_tuned_params
)
audio_data = result.get('wav')
if audio_data is not None:
audio_data = audio_data.tolist()
@@ -310,15 +329,15 @@ class Coqui:
del audio_data, sourceTensor, audio_tensor
if self.session['tts_engine'] != XTTSv2:
del tts
self._unload_tts(device, XTTSv2)
self._unload_tts(device, tts_internal_key)
if os.path.exists(file_path):
os.remove(file_path)
return voice_path
return new_voice_path
else:
error = f'No audio waveform found in _check_xtts_builtin_speakers() result: {result}'
print(error)
else:
error = f"_check_xtts_builtin_speakers() error: {XTTSv2} is None"
error = f"_check_xtts_builtin_speakers() error: {XTTSv2} is False"
print(error)
else:
error = f'The translated {default_text_file} could not be found! Voice cloning file will stay in English.'
@@ -344,11 +363,13 @@ class Coqui:
tts_internal_key = f"{BARK}-internal"
hf_repo = models[BARK]['internal']['repo']
hf_sub =models[BARK]['internal']['sub']
text_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][0]}", cache_dir=self.cache_dir)
coarse_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][1]}", cache_dir=self.cache_dir)
fine_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][2]}", cache_dir=self.cache_dir)
checkpoint_dir = os.path.dirname(text_model_path)
tts = self._load_checkpoint(tts_engine=BARK, key=tts_internal_key, checkpoint_dir=checkpoint_dir, device=device)
tts = (loaded_tts.get(tts_internal_key) or {}).get('engine', False)
if not tts:
text_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][0]}", cache_dir=self.cache_dir)
coarse_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][1]}", cache_dir=self.cache_dir)
fine_model_path = hf_hub_download(repo_id=hf_repo, filename=f"{hf_sub}{models[BARK]['internal']['files'][2]}", cache_dir=self.cache_dir)
checkpoint_dir = os.path.dirname(text_model_path)
tts = self._load_checkpoint(tts_engine=BARK, key=tts_internal_key, checkpoint_dir=checkpoint_dir, device=device)
if tts:
voice_temp = os.path.splitext(npz_file)[0]+'.wav'
shutil.copy(voice_path, voice_temp)
@@ -362,16 +383,16 @@ class Coqui:
}.items()
if self.session.get(key) is not None
}
#with torch.no_grad():
torch.manual_seed(67878789)
audio_data = tts.synthesize(
default_text,
loaded_tts[tts_internal_key]['config'],
speaker_id=speaker,
voice_dirs=bark_dir,
silent=True,
**fine_tuned_params
)
with torch.no_grad():
torch.manual_seed(67878789)
audio_data = tts.synthesize(
default_text,
loaded_tts[tts_internal_key]['config'],
speaker_id=speaker,
voice_dirs=bark_dir,
silent=True,
**fine_tuned_params
)
os.remove(voice_temp)
del audio_data
if self.session['tts_engine'] != BARK:
@@ -381,7 +402,7 @@ class Coqui:
print(msg)
return True
else:
error = f'_check_bark_npz() error: {tts_internal_key} is None'
error = f'_check_bark_npz() error: {tts_internal_key} is False'
print(error)
else:
return True
@@ -601,14 +622,14 @@ class Coqui:
}.items()
if self.session.get(key) is not None
}
#ith torch.no_grad():
result = tts.inference(
text=text_part,
language=self.session['language_iso1'],
gpt_cond_latent=settings['gpt_cond_latent'],
speaker_embedding=settings['speaker_embedding'],
**fine_tuned_params
)
with torch.no_grad():
result = tts.inference(
text=text_part,
language=self.session['language_iso1'],
gpt_cond_latent=settings['gpt_cond_latent'],
speaker_embedding=settings['speaker_embedding'],
**fine_tuned_params
)
audio_part = result.get('wav')
if self._is_valid(audio_part):
audio_part = audio_part.tolist()
@@ -627,9 +648,7 @@ class Coqui:
[MAN] and [WOMAN] to bias Bark toward male and female speakers, respectively
'''
bark_dir = os.path.join(os.path.dirname(settings['voice_path']), 'bark')
if self._check_bark_npz(settings['voice_path'], bark_dir, speaker, self.session['device']):
# text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
# waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
if self._check_bark_npz(settings['voice_path'], bark_dir, speaker, self.session['device']):
fine_tuned_params = {
key: cast_type(self.session[key])
for key, cast_type in {
@@ -638,8 +657,6 @@ class Coqui:
}.items()
if self.session.get(key) is not None
}
#with torch.no_grad():
torch.manual_seed(67878789)
npz = os.path.join(bark_dir, speaker, f'{speaker}.npz')
if self.npz_path is None or self.npz_path != npz:
self.npz_path = npz
@@ -649,82 +666,20 @@ class Coqui:
self.npz_data["coarse_prompt"],
self.npz_data["fine_prompt"]
]
audio_part, _ = tts.generate_audio(
text_part,
history_prompt=history_prompt,
silent=True,
**fine_tuned_params
)
with torch.no_grad():
torch.manual_seed(67878789)
audio_part, _ = tts.generate_audio(
text_part,
history_prompt=history_prompt,
silent=True,
**fine_tuned_params
)
if self._is_valid(audio_part):
audio_part = audio_part.tolist()
else:
error = 'Could not create npz file!'
print(error)
return False
elif self.session['tts_engine'] == TACOTRON2:
speaker_argument = {}
if settings['voice_path'] is not None:
proc_dir = os.path.join(self.session['voice_dir'], 'proc')
os.makedirs(proc_dir, exist_ok=True)
tmp_in_wav = os.path.join(proc_dir, f"{uuid.uuid4()}.wav")
tmp_out_wav = os.path.join(proc_dir, f"{uuid.uuid4()}.wav")
tts.tts_to_file(
text=text_part,
file_path=tmp_in_wav,
**speaker_argument
)
if settings['voice_path'] in settings['semitones'].keys():
semitones = settings['semitones'][settings['voice_path']]
else:
voice_path_gender = self._detect_gender(settings['voice_path'])
voice_builtin_gender = self._detect_gender(tmp_in_wav)
msg = f"Cloned voice seems to be {voice_path_gender}\nBuiltin voice seems to be {voice_builtin_gender}"
print(msg)
if voice_builtin_gender != voice_path_gender:
semitones = -4 if voice_path_gender == 'male' else 4
msg = f"Adapting builtin voice frequencies from the clone voice..."
print(msg)
else:
semitones = 0
settings['semitones'][settings['voice_path']] = semitones
if semitones > 0:
try:
cmd = [
shutil.which('sox'), tmp_in_wav,
"-r", str(settings['sample_rate']), tmp_out_wav,
"pitch", str(semitones * 100)
]
subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
except subprocess.CalledProcessError as e:
print(f"Subprocess error: {e.stderr}")
DependencyError(e)
return False
except FileNotFoundError as e:
print(f"File not found: {e}")
DependencyError(e)
return False
else:
tmp_out_wav = tmp_in_wav
#with torch.no_grad():
if tts_vc:
audio_part = tts_vc.voice_conversion(
source_wav=tmp_out_wav,
target_wav=settings['voice_path']
)
else:
error = f'Engine {self.tts_vc_key} is None'
print(error)
return False
settings['sample_rate'] = 16000
if os.path.exists(tmp_in_wav):
os.remove(tmp_in_wav)
if os.path.exists(tmp_out_wav):
os.remove(tmp_out_wav)
else:
audio_part = tts.tts(
text=text_part,
**speaker_argument
)
elif self.session['tts_engine'] == VITS:
speaker_argument = {}
if self.session['language'] == 'eng' and 'vctk/vits' in models[self.session['tts_engine']]['internal']['sub']:
@@ -775,7 +730,6 @@ class Coqui:
return False
else:
tmp_out_wav = tmp_in_wav
#with torch.no_grad():
if tts_vc:
audio_part = tts_vc.voice_conversion(
source_wav=tmp_out_wav,
@@ -838,7 +792,6 @@ class Coqui:
return False
else:
tmp_out_wav = tmp_in_wav
#with torch.no_grad():
if tts_vc:
audio_part = tts_vc.voice_conversion(
source_wav=tmp_out_wav,
@@ -856,6 +809,69 @@ class Coqui:
audio_part = tts.tts(
text=text_part
)
elif self.session['tts_engine'] == TACOTRON2:
speaker_argument = {}
if settings['voice_path'] is not None:
proc_dir = os.path.join(self.session['voice_dir'], 'proc')
os.makedirs(proc_dir, exist_ok=True)
tmp_in_wav = os.path.join(proc_dir, f"{uuid.uuid4()}.wav")
tmp_out_wav = os.path.join(proc_dir, f"{uuid.uuid4()}.wav")
tts.tts_to_file(
text=text_part,
file_path=tmp_in_wav,
**speaker_argument
)
if settings['voice_path'] in settings['semitones'].keys():
semitones = settings['semitones'][settings['voice_path']]
else:
voice_path_gender = self._detect_gender(settings['voice_path'])
voice_builtin_gender = self._detect_gender(tmp_in_wav)
msg = f"Cloned voice seems to be {voice_path_gender}\nBuiltin voice seems to be {voice_builtin_gender}"
print(msg)
if voice_builtin_gender != voice_path_gender:
semitones = -4 if voice_path_gender == 'male' else 4
msg = f"Adapting builtin voice frequencies from the clone voice..."
print(msg)
else:
semitones = 0
settings['semitones'][settings['voice_path']] = semitones
if semitones > 0:
try:
cmd = [
shutil.which('sox'), tmp_in_wav,
"-r", str(settings['sample_rate']), tmp_out_wav,
"pitch", str(semitones * 100)
]
subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
except subprocess.CalledProcessError as e:
print(f"Subprocess error: {e.stderr}")
DependencyError(e)
return False
except FileNotFoundError as e:
print(f"File not found: {e}")
DependencyError(e)
return False
else:
tmp_out_wav = tmp_in_wav
if tts_vc:
audio_part = tts_vc.voice_conversion(
source_wav=tmp_out_wav,
target_wav=settings['voice_path']
)
else:
error = f'Engine {self.tts_vc_key} is None'
print(error)
return False
settings['sample_rate'] = 16000
if os.path.exists(tmp_in_wav):
os.remove(tmp_in_wav)
if os.path.exists(tmp_out_wav):
os.remove(tmp_out_wav)
else:
audio_part = tts.tts(
text=text_part,
**speaker_argument
)
elif self.session['tts_engine'] == YOURTTS:
trim_audio_buffer = 0.005
speaker_argument = {}
@@ -866,12 +882,12 @@ class Coqui:
else:
voice_key = default_yourtts_settings['voices']['ElectroMale-2']
speaker_argument = {"speaker": voice_key}
#with torch.no_grad():
audio_part = tts.tts(
text=text_part,
language=language,
**speaker_argument
)
with torch.no_grad():
audio_part = tts.tts(
text=text_part,
language=language,
**speaker_argument
)
if self._is_valid(audio_part):
sourceTensor = self._tensor_type(audio_part)
audio_tensor = sourceTensor.clone().detach().unsqueeze(0).cpu()

1
lib/conf.py
View File

@@ -27,6 +27,7 @@ os.environ['XDG_CACHE_HOME'] = models_dir
os.environ['ARGOS_TRANSLATE_PACKAGE_PATH'] = os.path.join(models_dir, 'argostranslate')
os.environ['HF_TOKEN_PATH'] = os.path.join(os.path.expanduser('~'), '.huggingface_token')
os.environ['TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD'] = '1'
os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1'
os.environ['SUNO_OFFLOAD_CPU'] = 'False' # BARK option: False needs A GPU
os.environ['SUNO_USE_SMALL_MODELS'] = 'False' # BARK option: False needs a GPU with VRAM > 4GB
if platform.system() == 'Windows':

15
lib/functions.py
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@@ -8,6 +8,7 @@
import argparse
import asyncio
import csv
import jieba
import ebooklib
import fnmatch
import gc
@@ -40,6 +41,9 @@ import lib.conf as conf
import lib.lang as lang
import lib.models as mod
from soynlp.tokenizer import LTokenizer
from pythainlp.tokenize import word_tokenize
from sudachipy import dictionary, tokenizer
from tqdm import tqdm
from bs4 import BeautifulSoup
from collections import Counter
@@ -453,7 +457,7 @@ def normalize_text(text, lang, lang_iso1, tts_engine):
# Replace multiple and spaces with single space
text = re.sub(r'[ ]+', ' ', text)
# Replace ok by 'Owkey'
text = re.sub(r'\bok\b', '"O.K."', text, flags=re.IGNORECASE)
text = re.sub(r'\bok\b', 'Okay', text, flags=re.IGNORECASE)
# Replace parentheses with double quotes
text = re.sub(r'\(([^)]+)\)', r'"\1"', text)
# Escape special characters in the punctuation list for regex
@@ -731,19 +735,15 @@ def get_sentences(text, lang, tts_engine):
def segment_ideogramms(text):
if lang == 'zho':
import jieba
return list(jieba.cut(text))
elif lang == 'jpn':
from sudachipy import dictionary, tokenizer
sudachi = dictionary.Dictionary().create()
mode = tokenizer.Tokenizer.SplitMode.C
return [m.surface() for m in sudachi.tokenize(text, mode)]
elif lang == 'kor':
from konlpy.tag import Kkma
kkma = Kkma()
return kkma.morphs(text)
ltokenizer = LTokenizer()
return ltokenizer.tokenize(text)
elif lang in ['tha', 'lao', 'mya', 'khm']:
from pythainlp.tokenize import word_tokenize
return word_tokenize(text, engine='newmm')
else:
pattern_split = [re.escape(p) for p in punctuation_split_set]
@@ -994,6 +994,7 @@ def convert_chapters2audio(session):
start = sentence_number
msg = f'Block {chapter_num} containing {sentences_count} sentences...'
print(msg)
print(sentences)
for i, sentence in enumerate(sentences):
if session['cancellation_requested']:
msg = 'Cancel requested'

2
lib/lang.py
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File diff suppressed because one or more lines are too long

2
lib/models.py
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@@ -418,7 +418,7 @@ models = {
"thorsten/tacotron2-DDC": default_tacotron_settings['samplerate'],
"kokoro/tacotron2-DDC": default_tacotron_settings['samplerate'],
"ljspeech/tacotron2-DDC": default_tacotron_settings['samplerate'],
"baker/tacotron2-DDC-GST": default_tacotron_settings['samplerate']
"baker/tacotron2-DDC-GST": default_tacotron_settings['samplerate']
},
}
},

11
pyproject.toml
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@@ -29,10 +29,10 @@ dependencies = [
"hangul-romanize",
"indic-nlp-library",
"iso-639",
"jieba",
"mecab",
"mecab-python3",
"konlpy",
"jieba",
"mecab",
"mecab-python3",
"soynlp",
"pythainlp",
"pydub",
"m4b-util",
@@ -42,8 +42,7 @@ dependencies = [
"ray",
"regex",
"translate",
"tqdm",
"suno-bark",
"tqdm",
"unidic",
"pymupdf4llm",
"sudachipy",

6
requirements.txt
View File

@@ -10,13 +10,14 @@ gradio
hangul-romanize
indic-nlp-library
iso-639
jieba
jieba
mecab
mecab-python3
konlpy
soynlp
pythainlp
m4b-util
nvidia-ml-py
phonemizer-fork
pydub
PyOpenGL
pypinyin
@@ -24,7 +25,6 @@ ray
regex
translate
tqdm
suno-bark
unidic
pymupdf4llm
sudachipy