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import io |
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import gradio as gr |
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import torch |
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from modules.hf import spaces |
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from modules.webui.webui_utils import get_speakers, tts_generate |
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from modules.speaker import speaker_mgr, Speaker |
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import tempfile |
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def spk_to_tensor(spk): |
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spk = spk.split(" : ")[1].strip() if " : " in spk else spk |
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if spk == "None" or spk == "": |
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return None |
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return speaker_mgr.get_speaker(spk).emb |
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def get_speaker_show_name(spk): |
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if spk.gender == "*" or spk.gender == "": |
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return spk.name |
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return f"{spk.gender} : {spk.name}" |
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def merge_spk( |
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spk_a, |
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spk_a_w, |
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spk_b, |
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spk_b_w, |
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spk_c, |
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spk_c_w, |
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spk_d, |
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spk_d_w, |
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): |
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tensor_a = spk_to_tensor(spk_a) |
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tensor_b = spk_to_tensor(spk_b) |
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tensor_c = spk_to_tensor(spk_c) |
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tensor_d = spk_to_tensor(spk_d) |
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assert ( |
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tensor_a is not None |
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or tensor_b is not None |
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or tensor_c is not None |
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or tensor_d is not None |
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), "At least one speaker should be selected" |
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merge_tensor = torch.zeros_like( |
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tensor_a |
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if tensor_a is not None |
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else ( |
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tensor_b |
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if tensor_b is not None |
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else tensor_c if tensor_c is not None else tensor_d |
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) |
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) |
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total_weight = 0 |
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if tensor_a is not None: |
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merge_tensor += spk_a_w * tensor_a |
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total_weight += spk_a_w |
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if tensor_b is not None: |
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merge_tensor += spk_b_w * tensor_b |
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total_weight += spk_b_w |
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if tensor_c is not None: |
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merge_tensor += spk_c_w * tensor_c |
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total_weight += spk_c_w |
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if tensor_d is not None: |
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merge_tensor += spk_d_w * tensor_d |
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total_weight += spk_d_w |
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if total_weight > 0: |
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merge_tensor /= total_weight |
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merged_spk = Speaker.from_tensor(merge_tensor) |
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merged_spk.name = "<MIX>" |
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return merged_spk |
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@torch.inference_mode() |
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@spaces.GPU |
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def merge_and_test_spk_voice( |
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spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w, test_text |
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): |
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merged_spk = merge_spk( |
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spk_a, |
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spk_a_w, |
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spk_b, |
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spk_b_w, |
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spk_c, |
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spk_c_w, |
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spk_d, |
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spk_d_w, |
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) |
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return tts_generate( |
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spk=merged_spk, |
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text=test_text, |
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) |
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@torch.inference_mode() |
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@spaces.GPU |
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def merge_spk_to_file( |
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spk_a, |
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spk_a_w, |
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spk_b, |
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spk_b_w, |
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spk_c, |
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spk_c_w, |
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spk_d, |
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spk_d_w, |
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speaker_name, |
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speaker_gender, |
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speaker_desc, |
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): |
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merged_spk = merge_spk( |
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spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w |
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) |
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merged_spk.name = speaker_name |
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merged_spk.gender = speaker_gender |
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merged_spk.desc = speaker_desc |
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with tempfile.NamedTemporaryFile(delete=False, suffix=".pt") as tmp_file: |
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torch.save(merged_spk, tmp_file) |
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tmp_file_path = tmp_file.name |
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return tmp_file_path |
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merge_desc = """ |
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## Speaker Merger |
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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： |
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### 1. 选择说话人 |
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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。 |
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### 2. 合成语音 |
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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。 |
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### 3. 保存说话人 |
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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。 |
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""" |
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def create_speaker_panel(): |
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speakers = get_speakers() |
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speaker_names = ["None"] + [get_speaker_show_name(speaker) for speaker in speakers] |
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with gr.Tabs(): |
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with gr.TabItem("Merger"): |
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gr.Markdown(merge_desc) |
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with gr.Row(): |
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with gr.Column(scale=5): |
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with gr.Row(): |
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with gr.Group(): |
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spk_a = gr.Dropdown( |
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choices=speaker_names, value="None", label="Speaker A" |
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) |
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spk_a_w = gr.Slider( |
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value=1, minimum=0, maximum=10, step=1, label="Weight A" |
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) |
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with gr.Group(): |
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spk_b = gr.Dropdown( |
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choices=speaker_names, value="None", label="Speaker B" |
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) |
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spk_b_w = gr.Slider( |
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value=1, minimum=0, maximum=10, step=1, label="Weight B" |
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) |
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with gr.Group(): |
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spk_c = gr.Dropdown( |
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choices=speaker_names, value="None", label="Speaker C" |
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) |
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spk_c_w = gr.Slider( |
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value=1, minimum=0, maximum=10, step=1, label="Weight C" |
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) |
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with gr.Group(): |
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spk_d = gr.Dropdown( |
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choices=speaker_names, value="None", label="Speaker D" |
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) |
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spk_d_w = gr.Slider( |
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value=1, minimum=0, maximum=10, step=1, label="Weight D" |
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) |
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with gr.Row(): |
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with gr.Column(scale=3): |
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with gr.Group(): |
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gr.Markdown("🎤Test voice") |
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with gr.Row(): |
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test_voice_btn = gr.Button( |
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"Test Voice", variant="secondary" |
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) |
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with gr.Column(scale=4): |
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test_text = gr.Textbox( |
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label="Test Text", |
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placeholder="Please input test text", |
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value="说话人合并测试 123456789 [uv_break] ok, test done [lbreak]", |
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) |
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output_audio = gr.Audio(label="Output Audio") |
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with gr.Column(scale=1): |
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with gr.Group(): |
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gr.Markdown("🗃️Save to file") |
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speaker_name = gr.Textbox( |
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label="Name", value="forge_speaker_merged" |
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) |
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speaker_gender = gr.Textbox(label="Gender", value="*") |
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speaker_desc = gr.Textbox( |
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label="Description", value="merged speaker" |
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) |
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save_btn = gr.Button("Save Speaker", variant="primary") |
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merged_spker = gr.File( |
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label="Merged Speaker", interactive=False, type="binary" |
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) |
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test_voice_btn.click( |
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merge_and_test_spk_voice, |
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inputs=[ |
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spk_a, |
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spk_a_w, |
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spk_b, |
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spk_b_w, |
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spk_c, |
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spk_c_w, |
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spk_d, |
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spk_d_w, |
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test_text, |
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], |
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outputs=[output_audio], |
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) |
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save_btn.click( |
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merge_spk_to_file, |
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inputs=[ |
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spk_a, |
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spk_a_w, |
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spk_b, |
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spk_b_w, |
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spk_c, |
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spk_c_w, |
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spk_d, |
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spk_d_w, |
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speaker_name, |
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speaker_gender, |
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speaker_desc, |
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], |
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outputs=[merged_spker], |
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) |
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