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458import asyncio
import logging
import tempfile
from pathlib import Path
from subprocess import run
import requests
from pydub import AudioSegment
from wyoming.client import AsyncTcpClient
from wyoming.tts import Synthesize
from audiobook_generator.config.general_config import GeneralConfig
from audiobook_generator.core.audio_tags import AudioTags
from audiobook_generator.tts_providers.base_tts_provider import BaseTTSProvider
from audiobook_generator.utils.docker_helper import get_container, get_docker_client, is_env_var_equal, \
remove_container, wait_until_initialised
from audiobook_generator.utils.utils import set_audio_tags
logger = logging.getLogger(__name__)
class PiperTTSProvider(BaseTTSProvider):
def __init__(self, config: GeneralConfig):
config.output_format = config.output_format or "mp3"
self.price = 0.000
self.docker_container_name = "piper"
self.docker_port = 10200
self.docker_values_checked = False
self.base_voice_model_url = "https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0"
super().__init__(config)
def __str__(self) -> str:
return f"PiperTTSProvider(config={self.config})"
def validate_config(self):
pass
def text_to_speech(self, text: str, output_file: str, audio_tags: AudioTags):
if self.config.piper_path:
logger.info("Local Piper installation selected")
self._text_to_speech_local(text, output_file, audio_tags)
else:
logger.info("Docker Piper selected")
self._text_to_speech_docker(text, output_file, audio_tags)
def _text_to_speech_docker(self, text: str, output_file: str, audio_tags: AudioTags):
def start_docker_container():
logger.info("Starting docker container")
container = get_docker_client().containers.run(
image=self.config.piper_docker_image,
name=self.docker_container_name,
detach=True,
ports={str(self.docker_port): self.docker_port},
environment={
"PUID": 1000,
"PGID": 1000,
"TZ": "Etc/UTC",
"PIPER_VOICE": f"{self.config.model_name}",
"PIPER_SPEAKER": int(self.config.piper_speaker),
"PIPER_NOISE_SCALE": float(self.config.piper_noise_scale),
"PIPER_NOISE_W_SCALE": float(self.config.piper_noise_w_scale),
"PIPER_LENGTH_SCALE": float(self.config.piper_length_scale),
"PIPER_SENTENCE_SILENCE": float(self.config.piper_sentence_silence),
}
)
wait_until_initialised(container, "done.")
return container
def get_docker_container():
container = get_container("piper")
if not container:
logger.info("Piper docker container not found")
container = start_docker_container()
return container
def check_docker_values_match():
if self.docker_values_checked:
return
logger.info("Checking docker values match")
container = get_docker_container()
values = {
"PIPER_VOICE": f"{self.config.model_name}",
"PIPER_SPEAKER": int(self.config.piper_speaker),
"PIPER_NOISE_SCALE": float(self.config.piper_noise_scale),
"PIPER_NOISE_W_SCALE": float(self.config.piper_noise_w_scale),
"PIPER_LENGTH_SCALE": float(self.config.piper_length_scale),
"PIPER_SENTENCE_SILENCE": float(self.config.piper_sentence_silence)
}
for key, val in values.items():
if not is_env_var_equal(container, key, str(val)):
logger.info(f"Environment variable {key} is not equal to {val}, re-deploying docker")
remove_container(container)
start_docker_container()
break
self.docker_values_checked = True
async def synthesize_speech(input_text: str):
client = AsyncTcpClient('localhost', 10200)
synthesize = Synthesize(text=input_text)
request_event = synthesize.event()
audio_data = bytearray()
sample_rate = 22050 # Default sample rate
sample_width = 2 # Default to 16-bit audio
channels = 1 # Default to mono
async with client:
await client.write_event(request_event)
while True:
response_event = await client.read_event()
if response_event is None:
break
if response_event.type == "audio-start":
sample_rate = response_event.data.get("rate", sample_rate)
sample_width = response_event.data.get("width", sample_width)
if sample_width > 4:
sample_width = sample_width // 8
channels = response_event.data.get("channels", channels)
elif response_event.type == "audio-chunk" and response_event.payload:
audio_data.extend(response_event.payload)
elif response_event.type == "audio-stop":
return AudioSegment(
data=bytes(audio_data),
sample_width=sample_width,
frame_rate=sample_rate,
channels=channels,
)
else:
logger.error(f"Unknown event type: {response_event.type}")
return None, sample_rate, sample_width, channels
# Start Text to Speech with Docker Piper
check_docker_values_match()
audio_segment = asyncio.run(synthesize_speech(text))
audio_segment.export(output_file, format=self.config.output_format)
if audio_tags:
set_audio_tags(output_file, audio_tags)
def _text_to_speech_local(self, text: str, output_file: str, audio_tags: AudioTags):
def check_piper_exists():
if not Path(self.config.piper_path).exists():
raise FileNotFoundError(f"Piper executable not found at {self.config.piper_path}")
def check_voice_model_present():
piper_root_path = Path(self.config.piper_path).parent
vmp = f"{piper_root_path}/espeak-ng-data/voices/{self.config.model_name}.onnx"
if Path(vmp).exists():
return vmp
return False
def download_voice_model():
model_segments = self.config.model_name.split("-")
language_short = self.config.model_name.split("_")[0]
language_long = model_segments[0]
voice = model_segments[1]
quality = model_segments[2]
piper_root_path = Path(self.config.piper_path).parent
voice_model_root_path = f"{piper_root_path}/espeak-ng-data/voices"
files_to_download = [
f"{self.base_voice_model_url}/{language_short}/{language_long}/{voice}/{quality}/{self.config.model_name}.onnx?download=true",
f"{self.base_voice_model_url}/{language_short}/{language_long}/{voice}/{quality}/{self.config.model_name}.onnx.json?download=true.json"
]
for url in files_to_download:
file_name = f"{self.config.model_name}.onnx"
file_path = Path(f"{voice_model_root_path}/{file_name}")
if not file_path.exists():
logger.info(f"Downloading {url} to {file_path}")
with requests.get(url, stream=True) as response:
response.raise_for_status()
with open(file_path, "wb") as file:
for chunk in response.iter_content(chunk_size=8192):
file.write(chunk)
logger.info(f"Finished downloading {url}")
else:
logger.info(f"{file_name} already exists, skipping download")
return f"{voice_model_root_path}/{self.config.model_name}.onnx"
# Start Text to Speech with local Piper
check_piper_exists()
voice_model_path = check_voice_model_present()
if not voice_model_path:
logger.info(f"Voice model {self.config.model_name} not found, downloading...")
voice_model_path = download_voice_model()
if not voice_model_path:
raise FileNotFoundError(f"Voice model {self.config.model_name} not found after download")
with tempfile.TemporaryDirectory() as tmpdirname:
logger.debug("created temporary directory %r", tmpdirname)
tmpfilename = Path(tmpdirname) / "piper.wav"
if not tmpfilename.exists():
tmpfilename.touch()
cmd = [
self.config.piper_path,
"--model",
voice_model_path,
"--speaker",
str(self.config.piper_speaker),
"--noise_scale",
str(self.config.piper_noise_scale),
" --noise_w",
str(self.config.piper_noise_w_scale),
"--sentence_silence",
str(self.config.piper_sentence_silence),
"--length_scale",
str(self.config.piper_length_scale),
"-f",
tmpfilename
]
logger.info(
f"Running Piper TTS command: {' '.join(str(arg) for arg in cmd)}"
)
run(
cmd,
input=text.encode("utf-8"),
)
# set audio tags, need to be done before conversion or opus won't work, not sure why
if audio_tags:
set_audio_tags(tmpfilename, audio_tags)
logger.info(
f"Piper TTS command completed, converting {tmpfilename} to {self.config.output_format} format"
)
# Convert the wav file to the desired format
AudioSegment.from_wav(tmpfilename).export(
output_file, format=self.config.output_format
)
logger.info(f"Conversion completed, output file: {output_file}")
def estimate_cost(self, total_chars):
return 0 # Piper is free
def get_break_string(self):
return "." # Four spaces as the default break string
def get_output_file_extension(self):
return self.config.output_format
def get_piper_supported_languages():
return list(voice_data.keys())
def get_piper_supported_voices(language: str):
if language not in voice_data:
raise ValueError(f"Language '{language}' is not supported.")
return list(voice_data[language].keys())
def get_piper_supported_qualities(language: str, voice_name: str):
if language not in voice_data:
raise ValueError(f"Language '{language}' is not supported.")
if voice_name not in voice_data[language]:
raise ValueError(f"Voice '{voice_name}' is not supported for language '{language}'.")
return list(voice_data[language][voice_name].keys())
def get_piper_supported_speakers(language: str, voice_name: str, quality: str):
if language not in voice_data:
raise ValueError(f"Language '{language}' is not supported.")
if voice_name not in voice_data[language]:
raise ValueError(f"Voice '{voice_name}' is not supported for language '{language}'.")
if quality not in voice_data[language][voice_name]:
raise ValueError(f"Quality '{quality}' is not supported for voice '{voice_name}' in language '{language}'.")
if voice_data[language][voice_name][quality] is None:
return ["0"]
return list(range(voice_data[language][voice_name][quality] + 1))
voice_data = {
"ar_JO": {
"kareem": {"low": None, "medium": None}
},
"ca_ES": {
"upc_ona": {"x_low": None, "medium": None},
"upc_pau": {"x_low": None}
},
"cs_CZ": {
"jirka": {"low": None, "medium": None}
},
"cy_GB": {
"gwryw_gogleddol": {"medium": None}
},
"da_DK": {
"talesyntese": {"medium": None}
},
"de_DE": {
"eva_k": {"x_low": None},
"karlsson": {"low": None},
"kerstin": {"low": None},
"mls": {"medium": None},
"pavoque": {"low": None},
"ramona": {"low": None},
"thorsten": {"low": None, "medium": None, "high": None},
"thorsten_emotional": {"medium": None}
},
"el_GR": {
"rapunzelina": {"low": None}
},
"en_GB": {
"alan": {"low": None, "medium": None},
"alba": {"medium": None},
"aru": {"medium": 11},
"cori": {"medium": None, "high": None},
"jenny_dioco": {"medium": None},
"northern_english_male": {"medium": None},
"semaine": {"medium": 3},
"southern_english_female": {"low": None},
"vctk": {"medium": 108}
},
"en_US": {
"amy": {"low": None, "medium": None},
"arctic": {"medium": 17},
"bryce": {"medium": None},
"danny": {"low": None},
"hfc_female": {"medium": None},
"hfc_male": {"medium": None},
"joe": {"medium": None},
"john": {"medium": None},
"kathleen": {"low": None},
"kristin": {"medium": None},
"kusal": {"medium": None},
"l2arctic": {"medium": 23},
"lessac": {"low": None, "medium": None, "high": None},
"libritts": {"high": 903},
"libritts_r": {"medium": 903},
"ljspeech": {"medium": None, "high": None},
"norman": {"medium": None},
"ryan": {"low": None, "medium": None, "high": None}
},
"es_ES": {
"carlfm": {"x_low": None},
"davefx": {"medium": None},
"mls_10246": {"low": None},
"mls_9972": {"low": None},
"sharvard": {"medium": 1}
},
"es_MX": {
"ald": {"medium": None},
"claude": {"high": None}
},
"fa_IR": {
"amir": {"medium": None},
"gyro": {"medium": None}
},
"fi_FI": {
"harri": {"low": None, "medium": None}
},
"fr_FR": {
"gilles": {"low": None},
"mls": {"medium": 124},
"mls_1840": {"low": None},
"siwis": {"low": None, "medium": None},
"tom": {"medium": None},
"upmc": {"medium": 1}
},
"hu_HU": {
"anna": {"medium": None},
"berta": {"medium": None},
"imre": {"medium": None}
},
"is_IS": {
"bui": {"medium": None},
"salka": {"medium": None},
"steinn": {"medium": None},
"ugla": {"medium": None}
},
"it_IT": {
"paola": {"medium": None},
"riccardo": {"x_low": None}
},
"ka_GE": {
"natia": {"medium": None}
},
"kk_KZ": {
"iseke": {"x_low": None},
"issai": {"high": 5},
"raya": {"x_low": None}
},
"lb_LU": {
"marylux": {"medium": None}
},
"ne_NP": {
"google": {"x_low": 17, "medium": 17}
},
"nl_BE": {
"nathalie": {"x_low": None, "medium": None},
"rdh": {"x_low": None, "medium": None}
},
"nl_NL": {
"mls": {"medium": 51},
"mls_5809": {"low": None},
"mls_7432": {"low": None}
},
"no_NO": {
"talesyntese": {"medium": None}
},
"pl_PL": {
"darkman": {"medium": None},
"gosia": {"medium": None},
"mc_speech": {"medium": None},
"mls_6892": {"low": None}
},
"pt_BR": {
"edresson": {"low": None},
"faber": {"medium": None}
},
"pt_PT": {
"tugаo": {"medium": None}
},
"ro_RO": {
"mihai": {"medium": None}
},
"ru_RU": {
"denis": {"medium": None},
"dmitri": {"medium": None},
"irina": {"medium": None},
"ruslan": {"medium": None}
},
"sk_SK": {
"lili": {"medium": None}
},
"sl_SI": {
"artur": {"medium": None}
},
"sr_RS": {
"serbski_institut": {"medium": 1}
},
"sv_SE": {
"nst": {"medium": None}
},
"sw_CD": {
"lanfrica": {"medium": None}
},
"tr_TR": {
"dfki": {"medium": None},
"fahrettin": {"medium": None},
"fettah": {"medium": None}
},
"uk_UA": {
"lada": {"x_low": None},
"ukrainian_tts": {"medium": 2}
},
"vi_VN": {
"25hours_single": {"low": None},
"vais1000": {"medium": None},
"vivos": {"x_low": 64}
},
"zh_CN": {
"huayan": {"x_low": None, "medium": None}
}
}