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import json
from logging import getLogger
from typing import Any, Dict, List
import numpy as np
from pyopenjtalk import tts
from scipy.signal import resample
DUMMY_TEXT = "これはダミーのテキストです"
def initialize(path: str, use_gpu: bool, *args: List[Any]) -> None:
pass
def yukarin_s_forward(length: int, **kwargs: Dict[str, Any]) -> np.ndarray:
logger = getLogger("uvicorn") # FastAPI / Uvicorn 内からの利用のため
logger.info(
"Sorry, yukarin_s_forward() is a mock. Return values are incorrect.",
)
return np.ones(length) / 5
def yukarin_sa_forward(length: int, **kwargs: Dict[str, Any]) -> np.ndarray:
logger = getLogger("uvicorn") # FastAPI / Uvicorn 内からの利用のため
logger.info(
"Sorry, yukarin_sa_forward() is a mock. Return values are incorrect.",
)
return np.ones((1, length)) * 5
def decode_forward(length: int, **kwargs: Dict[str, Any]) -> np.ndarray:
"""
合成音声の波形データをNumPy配列で返します。ただし、常に固定の文言を読み上げます（DUMMY_TEXT）
参照→SynthesisEngine のdocstring [Mock]
Parameters
----------
length : int
フレームの長さ
Returns
-------
wave : np.ndarray
音声合成した波形データ
Note
-------
ここで行う音声合成では、調声（ピッチ等）を反映しない
また、入力内容によらず常に固定の文言を読み上げる
# pyopenjtalk.tts()の出力仕様
dtype=np.float64, 16 bit, mono 48000 Hz
# resampleの説明
非モックdecode_forwardと合わせるために、出力を24kHzに変換した。
"""
logger = getLogger("uvicorn") # FastAPI / Uvicorn 内からの利用のため
logger.info(
"Sorry, decode_forward() is a mock. Return values are incorrect.",
)
wave, sr = tts(DUMMY_TEXT)
wave = resample(
wave.astype("int16"),
24000 * len(wave) // 48000,
)
return wave
def metas() -> str:
return json.dumps(
[
{
"name": "dummy1",
"styles": [
{"name": "style0", "id": 0},
{"name": "style1", "id": 2},
{"name": "style2", "id": 4},
{"name": "style3", "id": 6},
],
"speaker_uuid": "7ffcb7ce-00ec-4bdc-82cd-45a8889e43ff",
"version": "mock",
},
{
"name": "dummy2",
"styles": [
{"name": "style0", "id": 1},
{"name": "style1", "id": 3},
{"name": "style2", "id": 5},
{"name": "style3", "id": 7},
],
"speaker_uuid": "388f246b-8c41-4ac1-8e2d-5d79f3ff56d9",
"version": "mock",
},
{
"name": "dummy3",
"styles": [
{"name": "style0", "id": 8},
],
"speaker_uuid": "35b2c544-660e-401e-b503-0e14c635303a",
"version": "mock",
},
{
"name": "dummy4",
"styles": [
{"name": "style0", "id": 9},
],
"speaker_uuid": "b1a81618-b27b-40d2-b0ea-27a9ad408c4b",
"version": "mock",
},
]
)
def supported_devices() -> str:
return json.dumps(
{
"cpu": True,
"cuda": False,
}
)
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