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import io | |
from typing import Union | |
from modules.SentenceSplitter import SentenceSplitter | |
from modules.SynthesizeSegments import SynthesizeSegments, combine_audio_segments | |
from modules import generate_audio as generate | |
from modules.speaker import Speaker | |
from modules.ssml_parser.SSMLParser import SSMLSegment | |
from modules.utils import audio | |
def synthesize_audio( | |
text: str, | |
temperature: float = 0.3, | |
top_P: float = 0.7, | |
top_K: float = 20, | |
spk: Union[int, Speaker] = -1, | |
infer_seed: int = -1, | |
use_decoder: bool = True, | |
prompt1: str = "", | |
prompt2: str = "", | |
prefix: str = "", | |
batch_size: int = 1, | |
spliter_threshold: int = 100, | |
end_of_sentence="", | |
): | |
spliter = SentenceSplitter(spliter_threshold) | |
sentences = spliter.parse(text) | |
text_segments = [ | |
SSMLSegment( | |
text=s, | |
params={ | |
"temperature": temperature, | |
"top_P": top_P, | |
"top_K": top_K, | |
"spk": spk, | |
"infer_seed": infer_seed, | |
"use_decoder": use_decoder, | |
"prompt1": prompt1, | |
"prompt2": prompt2, | |
"prefix": prefix, | |
}, | |
) | |
for s in sentences | |
] | |
synthesizer = SynthesizeSegments( | |
batch_size=batch_size, eos=end_of_sentence, spliter_thr=spliter_threshold | |
) | |
audio_segments = synthesizer.synthesize_segments(text_segments) | |
combined_audio = combine_audio_segments(audio_segments) | |
return audio.pydub_to_np(combined_audio) | |