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import io |
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import tempfile |
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import gradio as gr |
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import torch |
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from modules.speaker import Speaker, speaker_mgr |
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from modules.utils.hf import spaces |
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from modules.webui import webui_config, webui_utils |
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from modules.webui.webui_utils import get_speakers, tts_generate |
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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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if tensor_a is None and tensor_b is None and tensor_c is None and tensor_d is None: |
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raise gr.Error("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(duration=120) |
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def merge_and_test_spk_voice( |
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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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progress=gr.Progress(track_tqdm=True), |
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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(spk=merged_spk, text=test_text, progress=progress) |
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@torch.inference_mode() |
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@spaces.GPU(duration=120) |
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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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def create_speaker_merger(): |
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def get_spk_choices(): |
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speakers, speaker_names = webui_utils.get_speaker_names() |
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speaker_names = ["None"] + speaker_names |
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return speaker_names |
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gr.Markdown("SPEAKER_MERGER_GUIDE") |
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def spk_picker(label_tail: str): |
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with gr.Row(): |
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spk_a = gr.Dropdown( |
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choices=get_spk_choices(), value="None", label=f"Speaker {label_tail}" |
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) |
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refresh_a_btn = gr.Button("🔄", variant="secondary") |
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def refresh_a(): |
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speaker_mgr.refresh_speakers() |
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speaker_names = get_spk_choices() |
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return gr.update(choices=speaker_names) |
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refresh_a_btn.click(refresh_a, outputs=[spk_a]) |
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spk_a_w = gr.Slider( |
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value=1, |
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minimum=0, |
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maximum=10, |
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step=0.1, |
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label=f"Weight {label_tail}", |
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) |
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return spk_a, spk_a_w |
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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, spk_a_w = spk_picker("A") |
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with gr.Group(): |
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spk_b, spk_b_w = spk_picker("B") |
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with gr.Group(): |
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spk_c, spk_c_w = spk_picker("C") |
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with gr.Group(): |
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spk_d, spk_d_w = spk_picker("D") |
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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=webui_config.localization.DEFAULT_SPEAKER_MERAGE_TEXT, |
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) |
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output_audio = gr.Audio( |
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label="Output Audio", format="mp3" |
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) |
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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(label="Name", value="forge_speaker_merged") |
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speaker_gender = gr.Textbox(label="Gender", value="*") |
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speaker_desc = gr.Textbox(label="Description", value="merged speaker") |
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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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