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 = "" 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“Test Text”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“Save Speaker”按钮来保存合成的说话人。保存后的说话人文件将显示在“Merged Speaker”栏中,供下载使用。 """ def get_spk_choices(): speakers = get_speakers() speaker_names = ["None"] + [get_speaker_show_name(speaker) for speaker in speakers] return speaker_names # 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_merger(): speaker_names = get_spk_choices() gr.Markdown(merge_desc) def spk_picker(label_tail: str): with gr.Row(): spk_a = gr.Dropdown( choices=speaker_names, value="None", label=f"Speaker {label_tail}" ) refresh_a_btn = gr.Button("🔄", variant="secondary") def refresh_a(): speaker_mgr.refresh_speakers() speaker_names = get_spk_choices() return gr.update(choices=speaker_names) refresh_a_btn.click(refresh_a, outputs=[spk_a]) spk_a_w = gr.Slider( value=1, minimum=0, maximum=10, step=0.1, label=f"Weight {label_tail}", ) return spk_a, spk_a_w with gr.Row(): with gr.Column(scale=5): with gr.Row(): with gr.Group(): spk_a, spk_a_w = spk_picker("A") with gr.Group(): spk_b, spk_b_w = spk_picker("B") with gr.Group(): spk_c, spk_c_w = spk_picker("C") with gr.Group(): spk_d, spk_d_w = spk_picker("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", format="mp3" ) 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], )