Spaces:
Running
on
Zero
Running
on
Zero
File size: 4,718 Bytes
01e655b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 |
import base64
from fastapi import HTTPException
import io
import soundfile as sf
from pydantic import BaseModel
from modules.api.Api import APIManager
from modules.utils.audio import apply_prosody_to_audio_data
from modules.normalization import text_normalize
from modules import generate_audio as generate
from modules.ssml import parse_ssml
from modules.SynthesizeSegments import (
SynthesizeSegments,
combine_audio_segments,
synthesize_segment,
)
from modules.api import utils as api_utils
class SynthesisInput(BaseModel):
text: str = ""
ssml: str = ""
class VoiceSelectionParams(BaseModel):
languageCode: str = "ZH-CN"
name: str = "female2"
style: str = ""
temperature: float = 0.3
topP: float = 0.7
topK: int = 20
seed: int = 42
class AudioConfig(BaseModel):
audioEncoding: api_utils.AudioFormat = "mp3"
speakingRate: float = 1
pitch: float = 0
volumeGainDb: float = 0
sampleRateHertz: int
batchSize: int = 1
spliterThreshold: int = 100
class GoogleTextSynthesizeRequest(BaseModel):
input: SynthesisInput
voice: VoiceSelectionParams
audioConfig: dict
class GoogleTextSynthesizeResponse(BaseModel):
audioContent: str
async def google_text_synthesize(request: GoogleTextSynthesizeRequest):
input = request.input
voice = request.voice
audioConfig = request.audioConfig
# 提取参数
language_code = voice.languageCode
voice_name = voice.name
infer_seed = voice.seed or 42
audio_format = audioConfig.get("audioEncoding", "mp3")
speaking_rate = audioConfig.get("speakingRate", 1)
pitch = audioConfig.get("pitch", 0)
volume_gain_db = audioConfig.get("volumeGainDb", 0)
batch_size = audioConfig.get("batchSize", 1)
spliter_threshold = audioConfig.get("spliterThreshold", 100)
# TODO sample_rate
sample_rate_hertz = audioConfig.get("sampleRateHertz", 24000)
params = api_utils.calc_spk_style(spk=voice.name, style=voice.style)
# TODO maybe need to change the sample rate
sample_rate = 24000
try:
if input.text:
# 处理文本合成逻辑
text = text_normalize(input.text, is_end=True)
sample_rate, audio_data = generate.generate_audio(
text,
temperature=(
voice.temperature
if voice.temperature
else params.get("temperature", 0.3)
),
top_P=voice.topP if voice.topP else params.get("top_p", 0.7),
top_K=voice.topK if voice.topK else params.get("top_k", 20),
spk=params.get("spk", -1),
infer_seed=infer_seed,
prompt1=params.get("prompt1", ""),
prompt2=params.get("prompt2", ""),
prefix=params.get("prefix", ""),
)
elif input.ssml:
# 处理SSML合成逻辑
segments = parse_ssml(input.ssml)
for seg in segments:
seg["text"] = text_normalize(seg["text"], is_end=True)
if len(segments) == 0:
raise HTTPException(
status_code=400, detail="The SSML text is empty or parsing failed."
)
synthesize = SynthesizeSegments(batch_size=batch_size)
audio_segments = synthesize.synthesize_segments(segments)
combined_audio = combine_audio_segments(audio_segments)
buffer = io.BytesIO()
combined_audio.export(buffer, format="wav")
buffer.seek(0)
audio_data = buffer.read()
else:
raise HTTPException(
status_code=400, detail="Either text or SSML input must be provided."
)
audio_data = apply_prosody_to_audio_data(
audio_data,
rate=speaking_rate,
pitch=pitch,
volume=volume_gain_db,
sr=sample_rate,
)
buffer = io.BytesIO()
sf.write(buffer, audio_data, sample_rate, format="wav")
buffer.seek(0)
if audio_format == "mp3":
buffer = api_utils.wav_to_mp3(buffer)
base64_encoded = base64.b64encode(buffer.read())
base64_string = base64_encoded.decode("utf-8")
return {
"audioContent": f"data:audio/{audio_format.lower()};base64,{base64_string}"
}
except Exception as e:
import logging
logging.exception(e)
raise HTTPException(status_code=500, detail=str(e))
def setup(app: APIManager):
app.post("/v1/google/text:synthesize", response_model=GoogleTextSynthesizeResponse)(
google_text_synthesize
)
|