Add application file

app.py

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+import gradio as gr
+import json
+import os
+import datetime
+
+# 模拟数据库或配置：路径与模型的对应关系
+# 在实际使用中，你可以根据文件名或文件夹来自动判断模型名称
+AUDIO_METADATA = {
+    "./audios/001_en_i_C4.wav": "phraseLDM",
+    "./ audios/001_en_i_raw.wav": "baseline_v1"
+}
+
+def load_random_audios():
+    # 实际开发中这里应该是随机逻辑
+    path_a = "./audios/001_en_i_C4.wav"
+    path_b = "./audios/001_en_i_raw.wav"
+    
+    # 获取对应的模型名称，如果没有匹配则显示 unknown
+    meta_a = {"model": AUDIO_METADATA.get(path_a, "unknown"), "path": path_a}
+    meta_b = {"model": AUDIO_METADATA.get(path_b, "unknown"), "path": path_b}
+    
+    return path_a, path_b, meta_a, meta_b
+
+def submit_evaluation(preference, a_harm, a_nat, a_crea, a_mus, b_harm, b_nat, b_crea, b_mus, state_a, state_b):
+    # 构造你要求的 JSON 格式
+    result_entry = {
+        "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "audio_A": {
+            "model": state_a["model"],
+            "audio_path": state_a["path"],
+            "Harmonious": a_harm,
+            "Naturalness": a_nat,
+            "Creativity": a_crea,
+            "Musicality": a_mus
+        },
+        "audio_B": {
+            "model": state_b["model"],
+            "audio_path": state_b["path"],
+            "Harmonious": b_harm,
+            "Naturalness": b_nat,
+            "Creativity": b_crea,
+            "Musicality": b_mus
+        },
+        "better": "A" if "Audio A" in preference else ("B" if "Audio B" in preference else "Equal/Neither")
+    }
+
+    # 持久化保存到 JSONL 文件 (每行一条记录，方便追加)
+    save_path = "eval_results.json"
+    with open(save_path, "a", encoding="utf-8") as f:
+        f.write(json.dumps(result_entry, ensure_ascii=False) + "\n")
+    
+    return f"✅ 评估已保存至 {save_path}！您可以刷新页面进行下一组测试。"
+
+with gr.Blocks(title="音频生成质量评估", theme=gr.themes.Soft()) as demo:
+    # 使用 gr.State 存储不显示在 UI 上的元数据
+    state_a = gr.State()
+    state_b = gr.State()
+
+    gr.Markdown("<h2 style='text-align: center;'>🎶 PhraseLDM 歌曲合成主观听感测试</h2>")
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### Audio A")
+            audio_a = gr.Audio(interactive=False)
+        with gr.Column():
+            gr.Markdown("### Audio B")
+            audio_b = gr.Audio(interactive=False)
+            
+    gr.HTML("<hr>")
+    preference = gr.Radio(choices=["Audio A", "Audio B", "Both Equal", "Neither"], label="你更喜欢哪个 audio？")
+    gr.HTML("<hr>")
+
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("#### 对音频 A 的打分")
+            a_harm = gr.Slider(1, 5, step=0.01, value=3, label="Harmonious")
+            a_nat = gr.Slider(1, 5, step=0.01, value=3, label="Naturalness")
+            a_crea = gr.Slider(1, 5, step=0.01, value=3, label="Creativity")
+            a_mus = gr.Slider(1, 5, step=0.01, value=3, label="Musicality (Overall)")
+            
+        with gr.Column():
+            gr.Markdown("#### 对音频 B 的打分")
+            b_harm = gr.Slider(1, 5, step=0.01, value=3, label="Harmonious")
+            b_nat = gr.Slider(1, 5, step=0.01, value=3, label="Naturalness")
+            b_crea = gr.Slider(1, 5, step=0.01, value=3, label="Creativity")
+            b_mus = gr.Slider(1, 5, step=0.01, value=3, label="Musicality (Overall)")
+
+    submit_btn = gr.Button("提交评估结果", variant="primary")
+    status_output = gr.Textbox(label="系统状态", interactive=False)
+
+    # 提交时传入 state
+    submit_btn.click(
+        fn=submit_evaluation,
+        inputs=[preference, a_harm, a_nat, a_crea, a_mus, b_harm, b_nat, b_crea, b_mus, state_a, state_b],
+        outputs=status_output
+    )
+    
+    # 初始化加载
+    demo.load(fn=load_random_audios, outputs=[audio_a, audio_b, state_a, state_b])
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio