last_version

app.py

@@ -11,10 +11,6 @@ except RuntimeError:
 sys.path.append(str(Path(__file__).parent))
 
 
-
-# 确保能找到项目模块
-sys.path.append(str(Path(__file__).parent))
-
 from pages import emotion_analyzer # 导入情绪分析页面和 Chatbot 页面
 
 def main():
@@ -27,7 +23,7 @@ def main():
     st.title("Audio Emotion Recognition System")
     st.write("This is a web application for audio emotion recognition.")
     
-    # 先只测试情绪分析页面
+    # 只测试情绪分析页面
     emotion_analyzer.show()
 
 if __name__ == "__main__":

components/visualizations.py

@@ -27,9 +27,11 @@ def plot_emotion_distribution(emotion_dict):
         polar=dict(
             radialaxis=dict(
                 visible=True,
-                range=[0, 1]  # 设置范围
+                range=[0, 0.3],  # 设置范围
+                tickvals=[0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3],  # 设置刻度
+                ticktext=['0%', '5%', '10%', '15%', '20%', '25%', '30%']  # 设置刻度标签
             )),
         showlegend=False
     )
 
-    st.plotly_chart(fig, use_container_width=True) 
+    st.plotly_chart(fig, use_container_width=True)

history/history.json

@@ -0,0 +1,142 @@
+[
+    {
+        "audio_file": "test.wav",
+        "transcript": "please go now and make sure they stay from away, come back as soon as you can",
+        "emotions": {
+            "Neutral": "11.89%",
+            "Joy": "16.05%",
+            "Sad": "14.53%",
+            "Angry": "14.88%",
+            "Surprised": "14.02%",
+            "Fearful": "14.50%",
+            "Disgusted": "14.13%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "please go now and make sure they stay from away, come back as soon as you can",
+        "emotions": {
+            "Neutral": "11.89%",
+            "Joy": "16.05%",
+            "Sad": "14.53%",
+            "Angry": "14.88%",
+            "Surprised": "14.02%",
+            "Fearful": "14.50%",
+            "Disgusted": "14.13%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "please go now and make sure they stay from away, come back as soon as you can",
+        "emotions": {
+            "Neutral": "11.89%",
+            "Joy": "16.05%",
+            "Sad": "14.53%",
+            "Angry": "14.88%",
+            "Surprised": "14.02%",
+            "Fearful": "14.50%",
+            "Disgusted": "14.13%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "please go now and make sure they stay from away, come back as soon as you can",
+        "emotions": {
+            "Neutral": "11.89%",
+            "Joy": "16.05%",
+            "Sad": "14.53%",
+            "Angry": "14.88%",
+            "Surprised": "14.02%",
+            "Fearful": "14.50%",
+            "Disgusted": "14.13%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "please go now and make sure they stay from away, come back as soon as you can",
+        "emotions": {
+            "Neutral": "11.89%",
+            "Joy": "16.05%",
+            "Sad": "14.53%",
+            "Angry": "14.88%",
+            "Surprised": "14.02%",
+            "Fearful": "14.50%",
+            "Disgusted": "14.13%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "Please go now, and make sure to stay safe on the way. Come back as soon as you can.",
+        "emotions": {
+            "Neutral": "11.93%",
+            "Joy": "16.90%",
+            "Sad": "14.75%",
+            "Angry": "14.36%",
+            "Surprised": "14.24%",
+            "Fearful": "14.24%",
+            "Disgusted": "13.57%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "test.wav",
+        "transcript": "Please go now, and make sure to stay safe on the way. Come back as soon as you can.",
+        "emotions": {
+            "Neutral": "54.73%",
+            "Joy": "5.80%",
+            "Sad": "29.00%",
+            "Angry": "2.24%",
+            "Surprised": "0.51%",
+            "Fearful": "6.93%",
+            "Disgusted": "0.78%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "en-US-DavisNeural_sad_2x(1).wav",
+        "transcript": "I am fine. Just thinking about some things, that's all.",
+        "emotions": {
+            "Neutral": "12.95%",
+            "Joy": "42.23%",
+            "Sad": "41.40%",
+            "Angry": "0.25%",
+            "Surprised": "0.75%",
+            "Fearful": "2.24%",
+            "Disgusted": "0.19%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "en-US-NancyNeural_sad_2x(1).wav",
+        "transcript": "I am fine. Just thinking about some things, that's all.",
+        "emotions": {
+            "Neutral": "13.23%",
+            "Joy": "43.65%",
+            "Sad": "39.48%",
+            "Angry": "0.28%",
+            "Surprised": "0.79%",
+            "Fearful": "2.35%",
+            "Disgusted": "0.22%"
+        },
+        "probabilities": null
+    },
+    {
+        "audio_file": "301_26.wav",
+        "transcript": "stayed in school you know not let the accident just distract me and not i wouldve remained in school i probably wouldnt have had kids early you know um",
+        "emotions": {
+            "Neutral": "16.10%",
+            "Joy": "0.46%",
+            "Sad": "81.54%",
+            "Angry": "0.30%",
+            "Surprised": "0.18%",
+            "Fearful": "1.24%",
+            "Disgusted": "0.17%"
+        },
+        "probabilities": null
+    }
+]

models/config.json

@@ -0,0 +1,118 @@
+{
+  "_name_or_path": "facebook/wav2vec2-base",
+  "activation_dropout": 0.0,
+  "adapter_attn_dim": null,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForPreTraining"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.05,
+  "conv_bias": false,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "sum",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.05,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.1,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.0,
+  "freeze_feat_extract_train": true,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.0,
+  "mask_channel_length": 10,
+  "mask_channel_min_space": 1,
+  "mask_channel_other": 0.0,
+  "mask_channel_prob": 0.0,
+  "mask_channel_selection": "static",
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 5,
+  "mask_time_min_masks": 2,
+  "mask_time_min_space": 1,
+  "mask_time_other": 0.0,
+  "mask_time_prob": 0.05,
+  "mask_time_selection": "static",
+  "model_type": "wav2vec2",
+  "no_mask_channel_overlap": false,
+  "no_mask_time_overlap": false,
+  "num_adapter_layers": 3,
+  "num_attention_heads": 12,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 12,
+  "num_negatives": 50,
+  "output_hidden_size": 768,
+  "pad_token_id": 0,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 32,
+  "xvector_output_dim": 512
+}

models/model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:68228ad3957d05effe3fc941e0c304d1ae960095c2689e5a4fc39ed9170d07b5
+size 819785044

utils/model_inference.py

@@ -20,7 +20,7 @@ import torch.nn as nn
 from transformers import AutoModelForSequenceClassification, AutoConfig, Wav2Vec2ForPreTraining
 
 class MultimodalClassifier(nn.Module):
-    def __init__(self, bert_ckpt_path, wav2vec2_config_path, wav2vec2_safetensors_path):
+    def __init__(self, wav2vec2_config_path):
         super().__init__()
         
         # **加载微调后的 BERT**
@@ -31,10 +31,10 @@ class MultimodalClassifier(nn.Module):
             nn.Dropout(0.5),
             nn.Linear(self.bert.config.hidden_size, self.bert.config.num_labels)
         )
-        try:
-            self.bert.load_state_dict(torch.load(bert_ckpt_path, map_location=torch.device("cpu")), strict=True)
-        except Exception as e:
-            print(f"❌ 加载 `{bert_ckpt_path}` 失败: {e}")
+        # try:
+        #     self.bert.load_state_dict(torch.load(bert_ckpt_path, map_location=torch.device("cpu")), strict=True)
+        # except Exception as e:
+        #     print(f"❌ 加载 `{bert_ckpt_path}` 失败: {e}")
             
         # **先加载 Wav2Vec2**
         config = AutoConfig.from_pretrained(wav2vec2_config_path, num_labels=7)
@@ -45,13 +45,13 @@ class MultimodalClassifier(nn.Module):
             nn.Dropout(0.5),
             nn.Linear(self.wav2vec2.config.hidden_size, self.wav2vec2.config.num_labels)
         )
-        # **加载 safetensors 权重**
-        from safetensors.torch import load_file
-        state_dict = load_file(wav2vec2_safetensors_path)
-        try:
-            self.wav2vec2.load_state_dict(state_dict, strict=False)
-        except Exception as e:
-            print(f"❌ 加载 `{wav2vec2_safetensors_path}` 失败: {e}")
+        # # **加载 safetensors 权重**
+        # from safetensors.torch import load_file
+        # state_dict = load_file(wav2vec2_safetensors_path)
+        # try:
+        #     self.wav2vec2.load_state_dict(state_dict, strict=False)
+        # except Exception as e:
+        #     print(f"❌ 加载 `{wav2vec2_safetensors_path}` 失败: {e}")
 
         # **拼接特征的分类头**
         self.classifier = nn.Sequential(
@@ -81,12 +81,15 @@ class MultimodalClassifier(nn.Module):
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # **定义路径**
-bert_ckpt_path = "bert_meld_finetune_model.pth"
-wav2vec2_config_path = "config.json"
-wav2vec2_safetensors_path = "wav2vec2.safetensors"
+wav2vec2_config_path = r"models/config.json"
+model_path = r"models/model.safetensors"
 
-# **加载模型**
-model = MultimodalClassifier(bert_ckpt_path, wav2vec2_config_path, wav2vec2_safetensors_path).to(device)
+# **加载模型及其参数**
+model = MultimodalClassifier(wav2vec2_config_path).to(device)
+
+state_dict = load_file(model_path)
+model.load_state_dict(state_dict, strict=True)
+model.to(device)
 model.eval()
 
 print("✅ 微调的 BERT + Wav2Vec2 模型加载成功！")
@@ -104,7 +107,7 @@ def preprocess_audio(audio_path):
     print(waveform)
     return waveform.to(device)
 
-labels = ["Neutral", "Happy", "Sad", "Angry", "Fearful", "Disgusted", "Surprised"]
+labels = ["Neutral", "Joy", "Sad", "Angry", "Surprised", "Fearful", "Disgusted"]
 
 def predict_emotion(text, audio):
     text_inputs = preprocess_text(text)
@@ -122,7 +125,7 @@ def generate_transcript(audio_file):
 
 def save_history(audio_file, transcript, emotions, probabilities):
     """保存分析历史记录到文件"""
-    history_file = "history.json"
+    history_file = r"history/history.json"
     
     if not os.path.exists(history_file):
         with open(history_file, 'w') as f: