Update app.py

app.py

@@ -47,54 +47,61 @@ print(sample1_audio_path)
 
 DIMENSIONS_DATA = [
     {
-        "title": "语义和语用特征",
-        "audio": sample1_audio_path,
+        "title": "Semantic and Pragmatic Features",
+        "audio": "sample1_audio_path",
         "sub_dims": [
-            "记忆一致性：人类在短上下文中记忆通常一致，不一致也会尝试自我修正（如提问）；机器则可能会出现上下文记忆不一致且无法察觉或修正（如遗忘掉关键信息坚持错误回答）", "逻辑连贯性：人类逻辑自然流畅，允许合理跳跃；机器逻辑转折生硬或自相矛盾（如：突然切换话题无过渡）",
-            "读音正确性：人类大部分情况下发音正确、自然，会结合语境使用、区分多音字；机器存在不自然的发音错误，且对多音字语境的判断能力有限", "多语言混杂：人类多语言混杂流畅，且带有语境色彩；机器多语言混杂生硬，无语言切换逻辑",
-            "语言不精确性：人类说话时倾向存在含糊表达：如“差不多”、“应该是吧”，且会出现自我修正的行为；机器的回应通常不存在模糊表达，回答准确、肯定", "填充词使用：人类填充词（如‘嗯’‘那个’）随机且带有思考痕迹；机器填充词规律重复或完全缺失",
-            "隐喻与语用用意：人类会使用隐喻、反语、委婉来表达多重含义；机器表达直白，仅能字面理解或生硬使用修辞，缺乏语义多样性"
+            "Memory Consistency: Human memory in short contexts is usually consistent and self-correcting (e.g., by asking questions); machines may show inconsistent context memory and fail to notice or correct errors (e.g., forgetting key information and persisting in wrong answers).",
+            "Logical Coherence: Human logic is naturally coherent and allows reasonable leaps; machine logic is abrupt or self-contradictory (e.g., sudden topic shifts without transitions).",
+            "Pronunciation Accuracy: Humans generally pronounce words correctly and naturally, distinguishing polyphonic characters based on context; machines often mispronounce or lack contextual judgment for polyphonic words.",
+            "Multilingual Mixing: Humans mix multiple languages fluently and contextually; machines mix languages rigidly, lacking logical language switching.",
+            "Linguistic Vagueness: Human speech tends to include vague expressions (e.g., “more or less,” “I guess”) and self-corrections; machine responses are typically precise and assertive.",
+            "Filler Word Usage: Human filler words (e.g., 'uh', 'like') appear randomly and show signs of thinking; machine fillers are either repetitive and patterned or completely absent.",
+            "Metaphor and Pragmatic Intent: Humans use metaphors, irony, and euphemisms to express layered meanings; machines interpret literally or use rhetorical devices awkwardly, lacking semantic richness."
         ],
-        "reference_scores": [5, 5, 5, 0, 5, 5, 0]
+        "reference_scores": [5, 5, 3, 3, 5, 5, 3]
     },
     {
-        "title": "非生理性副语言特征",
-        "audio": sample1_audio_path,
+        "title": "Non-Physiological Paralinguistic Features",
+        "audio": "sample1_audio_path",
         "sub_dims": [
-            "节奏：人类语速随语义起伏，偶尔卡顿或犹豫；机器节奏均匀，几乎无停顿或停顿机械", "语调：人类在表达如疑问、惊讶、强调时，音调会自然上扬或下降；机器语调单一或变化过于规律，不符合语境",
-            "重读：人类会有意识地加强重要词语，从而突出信息焦点；机器的词语强度一致性强，或出现强调部位异常", "辅助性发声：人类会发出符合语境的非语言声音，如笑声、叹气等；机器的辅助性发声语境错误或机械化，或完全无辅助性发声"
+            "Rhythm: Human speech rate varies with meaning, occasionally hesitating or pausing; machine rhythm is uniform, with little or mechanical pauses.",
+            "Intonation: Humans naturally raise or lower pitch to express questions, surprise, or emphasis; machine intonation is monotonous or overly patterned, mismatching the context.",
+            "Emphasis: Humans consciously stress key words to highlight important information; machines have uniform word emphasis or stress incorrect parts.",
+            "Auxiliary Vocalizations: Humans produce context-appropriate non-verbal sounds (e.g., laughter, sighs); machine non-verbal sounds are contextually incorrect, mechanical, or absent."
         ],
-        "reference_scores": [5, 5, 5, 5]
+        "reference_scores": [4, 5, 4, 3]
     },
     {
-        "title": "生理性副语言特征",
-        "audio": sample1_audio_path,
+        "title": "Physiological Paralinguistic Features",
+        "audio": "sample1_audio_path",
         "sub_dims": [
-            "微生理杂音：人类说话存在呼吸声、口水音、气泡音等无意识发声，且自然地穿插在语流节奏当中；机器没有微生理杂音、语音过于干净，或添加不自然杂音",
-            "发音不稳定性：人类存在一定不规则性（诸如连读、颤音、含糊发音、鼻音等）；机器发音过于标准或统一，缺乏个性", "口音：人类存在自然的地区口音或语音特征；机器带口音效果生硬"
+            "Micro-physiological Noise: Human speech includes unconscious physiological sounds like breathing, saliva, or bubbling, naturally woven into rhythm; machine speech is overly clean or adds unnatural noises.",
+            "Pronunciation Instability: Human pronunciation includes irregularities (e.g., linking, tremors, slurring, nasal sounds); machine pronunciation is overly standard and uniform, lacking personality.",
+            "Accent: Humans naturally exhibit regional accents or speech traits; machine accents sound forced or unnatural."
         ],
-        "reference_scores": [5, 4, 4]
+        "reference_scores": [3, 3, 4]
     },
     {
-        "title": "机械人格",
-        "audio": sample1_audio_path,
+        "title": "Mechanical Persona",
+        "audio": "sample1_audio_path",
         "sub_dims": [
-            "谄媚现象：人类会根据语境判断是否同意，有时提出不同意见；机器频繁同意、感谢、道歉，过度认同对方观点，缺乏真实互动感",
-            "书面化表达：人类表达灵活，；机器回应句式工整、规范，内容过于书面化、用词泛泛"
+            "Flattery: Humans assess context to agree or disagree, sometimes offering differing opinions; machines excessively agree, thank, or apologize, over-validating the other party and lacking authentic interaction.",
+            "Formalized Expression: Human speech is flexible; machine responses are formally structured, overly written, and use vague wording."
         ],
         "reference_scores": [5, 5]
     },
     {
-        "title": "情感表达",
-        "audio": sample1_audio_path,
+        "title": "Emotional Expression",
+        "audio": "sample1_audio_path",
         "sub_dims": [
-            "语义层面：人类能对悲伤、开心等语境有符合人类的情感反应；机器回应情绪淡漠，或情感词泛泛、脱离语境",
-            "声学层面：人类音调、音量、节奏等声学特征随情绪动态变化；机器情感语调模式化，或与语境不符"
+            "Semantic Level: Humans show appropriate emotional responses to contexts like sadness or joy; machines are emotionally flat, or use emotional words vaguely and out of context.",
+            "Acoustic Level: Human pitch, volume, and rhythm change dynamically with emotion; machine emotional tone is formulaic or mismatched with the context."
         ],
-        "reference_scores": [5, 5]
+        "reference_scores": [3, 3]
     }
 ]
 
+
 DIMENSION_TITLES = [d["title"] for d in DIMENSIONS_DATA]
 MAX_SUB_DIMS = max(len(d['sub_dims']) for d in DIMENSIONS_DATA)
 
@@ -543,7 +550,7 @@ def submit_question_and_advance(q_idx, d_idx, selections, final_choice, all_resu
             return init_q_updates + (all_results, gr.update(value=""))
         else:
             # 准备完整结果数据
-            result_str = "### 测试全部完成！\n\n你的提交结果概览：\n"
+            result_str = "### Test Finished!\n\nOverview of the submission：\n"
             for res in all_results:
                 result_str += f"##### 最终判断: **{res['selections'].get('final_choice', '未选择')}**\n"
                 for dim_title, dim_data in res['selections'].items():
@@ -756,11 +763,11 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {max-width: 960px
     }
 
     with welcome_page:
-        gr.Markdown("# AI 识破者\n你将听到一系列对话，请判断哪个回应者是 AI。")
-        start_btn = gr.Button("开始挑战", variant="primary")
+        gr.Markdown("# AI Detective\nListen to the following conversations. Please determine which respondent is an AI.")
+        start_btn = gr.Button("Start", variant="primary")
 
     with info_page:
-        gr.Markdown("## 请提供一些基本信息")
+        gr.Markdown("## Basic Information")
         username_input = gr.Textbox(label="用户名", placeholder="请输入你的昵称")
         age_input = gr.Radio(["18岁以下", "18-25岁", "26-35岁", "36-50岁", "50岁以上"], label="年龄")
         gender_input = gr.Radio(["男", "女", "其他"], label="性别")
@@ -770,7 +777,8 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {max-width: 960px
         submit_info_btn = gr.Button("提交并开始学习样例", variant="primary", interactive=False)
 
     with sample_page:
-
+        
+        
         gr.Markdown("## 样例分析\n请选择一个维度进行学习和打分练习。所有维度共用同一个样例音频。")
         sample_dimension_selector = gr.Radio(DIMENSION_TITLES, label="选择学习维度", value=DIMENSION_TITLES[0])
         with gr.Row():
@@ -801,7 +809,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {max-width: 960px
                       "- 完成所有维度后，请根据整体印象对回应方的身份做出做出“人类”或“机器人”的 **最终判断**。\n"
                       "- 你可以使用“上一维度”和“下一维度”按钮在5个维度间自由切换和修改分数。")
         go_to_test_btn = gr.Button("开始测试", variant="primary")
-
+        
     with test_page:
         gr.Markdown("## 正式测试")
         question_progress_text = gr.Markdown()