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import io
import gradio as gr
import torch
from modules.hf import spaces
from modules.webui.webui_utils import get_speakers, tts_generate
from modules.speaker import speaker_mgr, Speaker
import tempfile
def spk_to_tensor(spk):
spk = spk.split(" : ")[1].strip() if " : " in spk else spk
if spk == "None" or spk == "":
return None
return speaker_mgr.get_speaker(spk).emb
def get_speaker_show_name(spk):
if spk.gender == "*" or spk.gender == "":
return spk.name
return f"{spk.gender} : {spk.name}"
def merge_spk(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
):
tensor_a = spk_to_tensor(spk_a)
tensor_b = spk_to_tensor(spk_b)
tensor_c = spk_to_tensor(spk_c)
tensor_d = spk_to_tensor(spk_d)
assert (
tensor_a is not None
or tensor_b is not None
or tensor_c is not None
or tensor_d is not None
), "At least one speaker should be selected"
merge_tensor = torch.zeros_like(
tensor_a
if tensor_a is not None
else (
tensor_b
if tensor_b is not None
else tensor_c if tensor_c is not None else tensor_d
)
)
total_weight = 0
if tensor_a is not None:
merge_tensor += spk_a_w * tensor_a
total_weight += spk_a_w
if tensor_b is not None:
merge_tensor += spk_b_w * tensor_b
total_weight += spk_b_w
if tensor_c is not None:
merge_tensor += spk_c_w * tensor_c
total_weight += spk_c_w
if tensor_d is not None:
merge_tensor += spk_d_w * tensor_d
total_weight += spk_d_w
if total_weight > 0:
merge_tensor /= total_weight
merged_spk = Speaker.from_tensor(merge_tensor)
merged_spk.name = "<MIX>"
return merged_spk
@torch.inference_mode()
@spaces.GPU
def merge_and_test_spk_voice(
spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w, test_text
):
merged_spk = merge_spk(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
)
return tts_generate(
spk=merged_spk,
text=test_text,
)
@torch.inference_mode()
@spaces.GPU
def merge_spk_to_file(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
speaker_name,
speaker_gender,
speaker_desc,
):
merged_spk = merge_spk(
spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w
)
merged_spk.name = speaker_name
merged_spk.gender = speaker_gender
merged_spk.desc = speaker_desc
with tempfile.NamedTemporaryFile(delete=False, suffix=".pt") as tmp_file:
torch.save(merged_spk, tmp_file)
tmp_file_path = tmp_file.name
return tmp_file_path
merge_desc = """
## Speaker Merger
在本面板中，您可以选择多个说话人并指定他们的权重，合成新的语音并进行测试。以下是各个功能的详细说明：
### 1. 选择说话人
您可以从下拉菜单中选择最多四个说话人（A、B、C、D），每个说话人都有一个对应的权重滑块，范围从0到10。权重决定了每个说话人在合成语音中的影响程度。
### 2. 合成语音
在选择好说话人和设置好权重后，您可以在“测试文本”框中输入要测试的文本，然后点击“测试语音”按钮来生成并播放合成的语音。
### 3. 保存说话人
您还可以在右侧的“说话人信息”部分填写新的说话人的名称、性别和描述，并点击“保存说话人”按钮来保存合成的说话人。保存后的说话人文件将显示在“合成说话人”栏中，供下载使用。
"""
# 显示 a b c d 四个选择框，选择一个或多个，然后可以试音，并导出
def create_speaker_panel():
speakers = get_speakers()
speaker_names = ["None"] + [get_speaker_show_name(speaker) for speaker in speakers]
with gr.Tabs():
with gr.TabItem("Merger"):
gr.Markdown(merge_desc)
with gr.Row():
with gr.Column(scale=5):
with gr.Row():
with gr.Group():
spk_a = gr.Dropdown(
choices=speaker_names, value="None", label="Speaker A"
)
spk_a_w = gr.Slider(
value=1, minimum=0, maximum=10, step=1, label="Weight A"
)
with gr.Group():
spk_b = gr.Dropdown(
choices=speaker_names, value="None", label="Speaker B"
)
spk_b_w = gr.Slider(
value=1, minimum=0, maximum=10, step=1, label="Weight B"
)
with gr.Group():
spk_c = gr.Dropdown(
choices=speaker_names, value="None", label="Speaker C"
)
spk_c_w = gr.Slider(
value=1, minimum=0, maximum=10, step=1, label="Weight C"
)
with gr.Group():
spk_d = gr.Dropdown(
choices=speaker_names, value="None", label="Speaker D"
)
spk_d_w = gr.Slider(
value=1, minimum=0, maximum=10, step=1, label="Weight D"
)
with gr.Row():
with gr.Column(scale=3):
with gr.Group():
gr.Markdown("🎤Test voice")
with gr.Row():
test_voice_btn = gr.Button(
"Test Voice", variant="secondary"
)
with gr.Column(scale=4):
test_text = gr.Textbox(
label="Test Text",
placeholder="Please input test text",
value="说话人合并测试 123456789 [uv_break] ok, test done [lbreak]",
)
output_audio = gr.Audio(label="Output Audio")
with gr.Column(scale=1):
with gr.Group():
gr.Markdown("🗃️Save to file")
speaker_name = gr.Textbox(
label="Name", value="forge_speaker_merged"
)
speaker_gender = gr.Textbox(label="Gender", value="*")
speaker_desc = gr.Textbox(
label="Description", value="merged speaker"
)
save_btn = gr.Button("Save Speaker", variant="primary")
merged_spker = gr.File(
label="Merged Speaker", interactive=False, type="binary"
)
test_voice_btn.click(
merge_and_test_spk_voice,
inputs=[
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
test_text,
],
outputs=[output_audio],
)
save_btn.click(
merge_spk_to_file,
inputs=[
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
speaker_name,
speaker_gender,
speaker_desc,
],
outputs=[merged_spker],
)
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