diff --git a/Ref_Audio_Selector/common/__init__.py b/Ref_Audio_Selector/common/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/Ref_Audio_Selector/common/common.py b/Ref_Audio_Selector/common/common.py
new file mode 100644
index 0000000..f7de06d
--- /dev/null
+++ b/Ref_Audio_Selector/common/common.py
@@ -0,0 +1,67 @@
+from tools import my_utils
+import glob
+import os
+
+class RefAudioListManager:
+    def __init__(self, root_dir):
+        self.audio_dict = {'default': []}
+        absolute_root = os.path.abspath(root_dir)
+
+        for subdir, dirs, files in os.walk(absolute_root):
+            relative_path = os.path.relpath(subdir, absolute_root)
+
+            if relative_path == '.':
+                category = 'default'
+            else:
+                category = relative_path.replace(os.sep, '')
+
+            for file in files:
+                if file.endswith('.wav'):
+                    # 将相对路径转换为绝对路径
+                    audio_abs_path = os.path.join(subdir, file)
+                    self.audio_dict[category].append(audio_abs_path)
+
+    def get_audio_list(self):
+        return self.audio_dict
+
+    def get_flattened_audio_list(self):
+        all_audio_files = []
+        for category_audios in self.audio_dict.values():
+            all_audio_files.extend(category_audios)
+        return all_audio_files
+
+    def get_ref_audio_list(self):
+        audio_info_list = []
+        for category, audio_paths in self.audio_dict.items():
+            for audio_path in audio_paths:
+                filename_without_extension = os.path.splitext(os.path.basename(audio_path))[0]
+                audio_info = {
+                    'emotion': f"{category}-{filename_without_extension}",
+                    'ref_path': audio_path,
+                    'ref_text': filename_without_extension,
+                }
+                audio_info_list.append(audio_info)
+        return audio_info_list
+
+def batch_clean_paths(paths):
+    """
+    批量处理路径列表，对每个路径调用 clean_path() 函数。
+
+    参数:
+        paths (list[str]): 包含待处理路径的列表。
+
+    返回:
+        list[str]: 经过 clean_path() 处理后的路径列表。
+    """
+    cleaned_paths = []
+    for path in paths:
+        cleaned_paths.append(my_utils.clean_path(path))
+    return cleaned_paths
+
+
+def read_text_file_to_list(file_path):
+    # 按照UTF-8编码打开文件（确保能够正确读取中文）
+    with open(file_path, mode='r', encoding='utf-8') as file:
+        # 读取所有行并存储到一个列表中
+        lines = file.read().splitlines()
+    return lines
\ No newline at end of file
diff --git a/Ref_Audio_Selector/ref_audio_selector_webui.py b/Ref_Audio_Selector/ref_audio_selector_webui.py
index 6946fee..74f2f2a 100644
--- a/Ref_Audio_Selector/ref_audio_selector_webui.py
+++ b/Ref_Audio_Selector/ref_audio_selector_webui.py
@@ -1,7 +1,9 @@
 import os.path
 
 import gradio as gr
-import Ref_Audio_Selector.tool.ref_audio_opt as ref_audio_opt
+import Ref_Audio_Selector.tool.audio_similarity as audio_similarity
+import Ref_Audio_Selector.tool.audio_inference as audio_inference
+import Ref_Audio_Selector.common.common as common
 from tools.i18n.i18n import I18nAuto
 
 i18n = I18nAuto()
@@ -17,14 +19,14 @@ def check_base_info(text_work_space_dir, text_character):
 
 # 从list文件，提取参考音频
 def convert_from_list(text_work_space_dir, text_character, text_list_input):
-    ref_audio_all = os.path.join(text_work_space_dir, 'ref_audio_all')
-    text_convert_from_list_info = f"转换成功：生成目录${ref_audio_all}"
+    ref_audio_all = os.path.join(text_work_space_dir, 'refer_audio_all')
+    text_convert_from_list_info = f"转换成功：生成目录{ref_audio_all}"
     text_sample_dir = ref_audio_all
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_list_input is None or text_list_input == '':
             raise Exception(i18n("list文件路径不能为空"))
-        ref_audio_opt.convert_from_list(text_list_input, ref_audio_all)
+        audio_similarity.convert_from_list(text_list_input, ref_audio_all)
     except Exception as e:
         text_convert_from_list_info = f"发生异常：{e}"
         text_sample_dir = ''
@@ -34,8 +36,8 @@ def convert_from_list(text_work_space_dir, text_character, text_list_input):
 # 基于一个基准音频，从参考音频目录中进行分段抽样
 def sample(text_work_space_dir, text_character, text_sample_dir, text_base_voice_path,
            text_subsection_num, text_sample_num, checkbox_similarity_output):
-    text_sample_info = "抽样成功：生成目录XXX"
-    ref_audio_dir = "D：//tt"
+    ref_audio_dir = os.path.join(text_work_space_dir, 'refer_audio')
+    text_sample_info = f"抽样成功：生成目录{ref_audio_dir}"
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_sample_dir is None or text_sample_dir == '':
@@ -46,7 +48,14 @@ def sample(text_work_space_dir, text_character, text_sample_dir, text_base_voice
             raise Exception(i18n("分段数不能为空"))
         if text_sample_num is None or text_sample_num == '':
             raise Exception(i18n("每段随机抽样个数不能为空"))
-        pass
+
+        similarity_list = audio_similarity.start_similarity_analysis(text_work_space_dir, text_sample_dir, text_base_voice_path, checkbox_similarity_output)
+        
+        if similarity_list is None:
+            raise Exception(i18n("相似度分析失败"))
+        
+        audio_similarity.sample(ref_audio_dir, similarity_list, text_subsection_num, text_sample_num)
+        
     except Exception as e:
         text_sample_info = f"发生异常：{e}"
         ref_audio_dir = ''
@@ -61,8 +70,9 @@ def sample(text_work_space_dir, text_character, text_sample_dir, text_base_voice
 def model_inference(text_work_space_dir, text_character, text_model_inference_voice_dir, text_url,
                     text_text, text_ref_path, text_ref_text, text_emotion,
                     text_test_content):
-    text_model_inference_info = "推理成功：生成目录XXX"
-    text_asr_audio_dir = "D：//tt"
+    inference_dir = os.path.join(text_work_space_dir, 'inference_audio')
+    text_asr_audio_dir = os.path.join(inference_dir, 'text')
+    text_model_inference_info = f"推理成功：生成目录{inference_dir}"
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_model_inference_voice_dir is None or text_model_inference_voice_dir == '':
@@ -76,7 +86,15 @@ def model_inference(text_work_space_dir, text_character, text_model_inference_vo
         if (text_ref_path is None or text_ref_path == '') and (text_ref_text is None or text_ref_text == '') and (
                 text_emotion is None or text_emotion == ''):
             raise Exception(i18n("参考音频路径/文本和角色情绪二选一填写，不能全部为空"))
-        pass
+        url_composer = audio_inference.URLComposer(text_url, text_emotion, text_text, text_ref_path, text_ref_text)
+        url_composer.is_valid()
+        text_list = common.read_text_file_to_list(text_test_content)
+        if text_list is None or len(text_list) == 0:
+            raise Exception(i18n("待推理文本内容不能为空"))
+        ref_audio_manager = common.RefAudioListManager(text_model_inference_voice_dir)
+        if len(ref_audio_manager.get_audio_list()) == 0:
+            raise Exception(i18n("待推理的参考音频不能为空"))
+        audio_inference.generate_audio_files(url_composer, text_list, ref_audio_manager.get_ref_audio_list(), inference_dir)
     except Exception as e:
         text_model_inference_info = f"发生异常：{e}"
         text_asr_audio_dir = ''
@@ -86,8 +104,9 @@ def model_inference(text_work_space_dir, text_character, text_model_inference_vo
 # 对推理生成音频执行asr
 def asr(text_work_space_dir, text_character, text_asr_audio_dir, dropdown_asr_model,
         dropdown_asr_size, dropdown_asr_lang):
-    text_asr_info = "asr成功：生成目录XXX"
-    text_text_similarity_analysis_path = "D：//tt"
+    asr_file = os.path.join(text_work_space_dir, 'asr.list')
+    text_text_similarity_analysis_path = asr_file
+    text_asr_info = f"asr成功：生成文件asr.list"
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_asr_audio_dir is None or text_asr_audio_dir == '':
@@ -108,7 +127,8 @@ def asr(text_work_space_dir, text_character, text_asr_audio_dir, dropdown_asr_mo
 # 对asr生成的文件，与原本的文本内容，进行相似度分析
 def text_similarity_analysis(text_work_space_dir, text_character,
                              text_text_similarity_analysis_path):
-    text_text_similarity_analysis_info = "相似度分析成功：生成目录XXX"
+    similarity_file = os.path.join(text_work_space_dir, 'similarity.txt')
+    text_text_similarity_analysis_info = f"相似度分析成功：生成文件{similarity_file}"
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_text_similarity_analysis_path is None or text_text_similarity_analysis_path == '':
@@ -153,7 +173,8 @@ def sync_ref_audio(text_work_space_dir, text_character, text_sync_ref_audio_dir,
 
 # 根据模板和参考音频目录，生成参考音频配置内容
 def create_config(text_work_space_dir, text_character, text_template, text_sync_ref_audio_dir2):
-    text_create_config_info = "配置生成成功：生成目录XXX"
+    config_file = os.path.join(text_work_space_dir, 'refer_audio.json')
+    text_create_config_info = f"配置生成成功：生成文件{config_file}"
     try:
         check_base_info(text_work_space_dir, text_character)
         if text_template is None or text_template == '':
@@ -168,8 +189,12 @@ def create_config(text_work_space_dir, text_character, text_template, text_sync_
 
 # 基于请求路径和参数，合成完整的请求路径
 def whole_url(text_url, text_text, text_ref_path, text_ref_text, text_emotion):
-    text_whole_url = f'{text_url}?{text_text}=文本内容&{text_ref_path}=参考音频路径&{text_ref_text}=参考文本&{text_emotion}=情绪类型'
-    return [text_whole_url]
+    url_composer = audio_inference.URLComposer(text_url, text_emotion, text_text, text_ref_path, text_ref_text)
+    if url_composer.is_emotion():
+        text_whole_url = url_composer.build_url_with_emotion('测试内容','情绪类型')
+    else:
+        text_whole_url = url_composer.build_url_with_ref('测试内容','参考路径','参考文本')
+    return text_whole_url
 
 
 with gr.Blocks() as app:
diff --git a/Ref_Audio_Selector/tool/audio_inference.py b/Ref_Audio_Selector/tool/audio_inference.py
new file mode 100644
index 0000000..2c29122
--- /dev/null
+++ b/Ref_Audio_Selector/tool/audio_inference.py
@@ -0,0 +1,104 @@
+import os
+import requests
+import urllib.parse
+
+class URLComposer:
+    def __init__(self, base_url, emotion_param_name, text_param_name, ref_path_param_name, ref_text_param_name):
+        self.base_url = base_url
+        self.emotion_param_name = emotion_param_name
+        self.text_param_name = text_param_name
+        self.ref_path_param_name = ref_path_param_name
+        self.ref_text_param_name = ref_text_param_name
+        
+    
+    def is_valid(self):
+        if self.base_url is None or self.base_url == '':
+            raise ValueError("请输入url")
+        
+        if self.text_param_name is None or self.text_param_name == '':
+            raise ValueError("请输入text参数名")
+        
+        if self.emotion_param_name is None and self.ref_path_param_name is None and self.ref_text_param_name is None:
+            raise ValueError("请输入至少一个参考or情绪的参数")
+        
+    def is_emotion(self):
+        return self.emotion_param_name is not None and self.emotion_param_name != ''
+
+    def build_url_with_emotion(self, text_value, emotion_value):
+        if not self.emotion_param_name:
+            raise ValueError("Emotion parameter name is not set.")
+        params = {
+            self.text_param_name: urllib.parse.quote(text_value),
+            self.emotion_param_name: urllib.parse.quote(emotion_value),
+        }
+        return self._append_params_to_url(params)
+
+    def build_url_with_ref(self, text_value, ref_path_value, ref_text_value):
+        if self.emotion_param_name:
+            raise ValueError("Cannot use reference parameters when emotion parameter is set.")
+        params = {
+            self.text_param_name: urllib.parse.quote(text_value),
+            self.ref_path_param_name: urllib.parse.quote(ref_path_value),
+            self.ref_text_param_name: urllib.parse.quote(ref_text_value),
+        }
+        return self._append_params_to_url(params)
+
+    def _append_params_to_url(self, params: dict):
+        url_with_params = self.base_url
+        if params:
+            query_params = '&'.join([f"{k}={v}" for k, v in params.items()])
+            url_with_params += '?' + query_params if '?' not in self.base_url else '&' + query_params
+        return url_with_params
+    
+    
+def generate_audio_files(url_composer, text_list, emotion_list, output_dir_path):
+
+    # Ensure the output directory exists
+    output_dir = Path(output_dir_path)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    # Create subdirectories for text and emotion categories
+    text_subdir = os.path.join(output_dir, 'text')
+    text_subdir.mkdir(exist_ok=True)
+    emotion_subdir = os.path.join(output_dir, 'emotion')
+    emotion_subdir.mkdir(exist_ok=True)
+
+    for text, emotion in zip(text_list, emotion_list):
+        # Generate audio byte stream using the create_audio function
+        
+        if url_composer.is_emotion():
+            real_url = url_composer.build_url_with_emotion(text, emotion['emotion'])
+        else:
+            real_url = url_composer.build_url_with_ref(text, emotion['ref_path'], emotion['ref_text'])
+        
+        audio_bytes = inference_audio_from_api(real_url)
+
+        emotion_name = emotion['emotion']
+
+        # Save audio files in both directories with the desired structure
+        text_file_path = os.path.join(text_subdir, text, emotion_name, '.wav')
+        emotion_file_path = os.path.join(emotion_subdir, emotion_name, text, '.wav')
+
+        # Ensure intermediate directories for nested file paths exist
+        text_file_path.parent.mkdir(parents=True, exist_ok=True)
+        emotion_file_path.parent.mkdir(parents=True, exist_ok=True)
+
+        # Write audio bytes to the respective files
+        with open(text_file_path, 'wb') as f:
+            f.write(audio_bytes)
+        with open(emotion_file_path, 'wb') as f:
+            f.write(audio_bytes)
+    
+
+
+def inference_audio_from_api(url):
+
+    # 发起GET请求
+    response = requests.get(url, stream=True)
+
+    # 检查响应状态码是否正常（例如200表示成功）
+    if response.status_code == 200:
+        # 返回音频数据的字节流
+        return response.content
+    else:
+        raise Exception(f"Failed to fetch audio from API. Server responded with status code {response.status_code}.")
\ No newline at end of file
diff --git a/Ref_Audio_Selector/tool/audio_similarity.py b/Ref_Audio_Selector/tool/audio_similarity.py
new file mode 100644
index 0000000..9eb7172
--- /dev/null
+++ b/Ref_Audio_Selector/tool/audio_similarity.py
@@ -0,0 +1,182 @@
+import os
+import shutil
+from config import python_exec
+from subprocess import Popen
+
+def convert_from_list(list_file, output_dir):
+    # 创建输出目录，如果它不存在的话
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    # 解析.list文件，并操作文件
+    with open(list_file, 'r', encoding='utf-8') as file:
+        lines = file.readlines()
+
+    for line in lines:
+        parts = line.strip().split('|')
+        if len(parts) != 4:
+            print(f"Line format incorrect: {line}")
+            continue
+
+        audio_path, _, _, transcription = parts
+
+        # 构建新的文件名和路径
+        new_filename = transcription + '.wav'
+        # new_filename = new_filename.replace(' ', '_')  # 移除空格
+        # new_filename = ''.join(e for e in new_filename if e.isalnum() or e in ['_', '.'])  # 移除非法字符
+        new_path = os.path.join(output_dir, new_filename)
+
+        # 如果目标文件已存在，不要覆盖
+        if os.path.exists(new_path):
+            print(f"File already exists: {new_path}")
+            continue
+
+        try:
+            # 检查音频文件是否存在
+            if not os.path.exists(audio_path):
+                print(f"Audio file does not exist: {audio_path}")
+                continue
+
+            # 复制音频文件到output目录并重命名
+            shutil.copy2(audio_path, new_path)
+            print(f"File copied and renamed to: {new_path}")
+        except Exception as e:
+            print(f"An error occurred while processing: {audio_path}")
+            print(e)
+
+    print("Processing complete.")
+
+
+def sample(output_audio_dir, similarity_list, subsection_num, sample_num):
+    # 按照相似度分值降序排序相似度列表
+    similarity_list.sort(key=lambda x: x['score'], reverse=True)
+
+    # 计算每段的起始索引
+    step = len(similarity_list) // subsection_num
+    if len(similarity_list) % subsection_num != 0:
+        step += 1
+
+    # 分段并随机采样
+    for i in range(subsection_num):
+        start = i * step
+        end = (i + 1) * step
+        end = min(end, len(similarity_list))  # 防止最后一段越界
+        
+        num = min(sample_num, len(similarity_list[start:end]))
+
+        # 随机采样
+        random.shuffle(similarity_list[start:end])
+        sampled_subsection = similarity_list[start:start+num]
+
+        # 创建并进入子目录
+        subdir_name = f'subsection_{i+1}'
+        subdir_path = os.path.join(output_audio_dir, subdir_name)
+        os.makedirs(subdir_path, exist_ok=True)
+
+        # 复制采样结果的音频到子目录
+        for item in sampled_subsection:
+            src_path = item['wav_path']
+            dst_path = os.path.join(subdir_path, os.path.basename(src_path))
+            shutil.copyfile(src_path, dst_path)
+
+    print("Sampling completed.")
+
+
+
+def start_similarity_analysis(work_space_dir, sample_dir, base_voice_path, need_similarity_output):
+
+    similarity_list = None
+
+    similarity_dir = os.path.join(work_space_dir, 'similarity')
+    os.makedirs(similarity_dir, exist_ok=True)
+
+    base_voice_file_name = ref_audio_opt.get_filename_without_extension(base_voice_path)
+    similarity_file = os.path.join(similarity_dir, f'{base_voice_file_name}.txt')
+
+    global p_similarity
+    if(p_similarity==None):
+        cmd = f'"{python_exec}" tools/speaker_verification/audio_similarity.py '
+        cmd += f' -r "{base_voice_path}"'
+        cmd += f' -c "{sample_dir}"'
+        cmd += f' -o {similarity_file}'
+
+        print(cmd)
+        p_similarity = Popen(cmd, shell=True)
+        p_similarity.wait()
+
+        if need_similarity_output:
+            similarity_list = ref_audio_opt.parse_similarity_file(similarity_file)
+            similarity_file_dir = os.path.dirname(similarity_dir, base_voice_file_name)
+            ref_audio_opt.copy_and_move(similarity_file_dir, similarity_list)
+
+        p_similarity=None
+        return similarity_list
+    else:
+        return similarity_list
+
+
+def parse_similarity_file(file_path):
+    """
+    解析指定文本文件，将其中的内容以元组形式存入列表。
+
+    参数:
+        file_path (str): 待解析的文本文件路径。
+
+    返回:
+        list[tuple[float, str]]: 存储浮点数和路径的元组列表。
+    """
+    result_list = []
+
+    with open(file_path, 'r') as file:
+        for line in file:
+            # 去除行尾换行符并按'|'分割
+            score, filepath = line.strip().split('|')
+
+            # 将浮点数字符串转换为浮点数类型
+            score = float(score)
+
+            # 将得分和路径作为元组添加到结果列表
+            result_list.append({
+                'score': score,
+                'wav_path': filepath
+            })
+
+    return result_list
+
+
+def copy_and_move(output_audio_directory, similarity_scores):
+
+    # 确保新目录存在
+    if not os.path.exists(output_audio_directory):
+        os.makedirs(output_audio_directory)
+
+    # 遍历并复制文件
+    for item in similarity_scores:
+        # 构造新的文件名
+        base_name = os.path.basename(item['wav_path'])[:-4]  # 去掉.wav扩展名
+        new_name = f"{item['score']}-{base_name}.wav"
+
+        # 新文件的完整路径
+        new_path = os.path.join(output_audio_directory, new_name)
+
+        # 复制文件到新目录
+        shutil.copyfile(item['wav_path'], new_path)
+
+    print("已完成复制和重命名操作。")
+
+
+def get_filename_without_extension(file_path):
+    """
+    Given a file path string, returns the file name without its extension.
+
+    Parameters:
+    file_path (str): The full path to the file.
+
+    Returns:
+    str: The file name without its extension.
+    """
+    base_name = os.path.basename(file_path)  # Get the base name (file name with extension)
+    file_name, file_extension = os.path.splitext(base_name)  # Split the base name into file name and extension
+    return file_name  # Return the file name without extension
+
+
diff --git a/Ref_Audio_Selector/tool/ref_audio_opt.py b/Ref_Audio_Selector/tool/ref_audio_opt.py
deleted file mode 100644
index fb7bd7e..0000000
--- a/Ref_Audio_Selector/tool/ref_audio_opt.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import os
-import shutil
-
-
-def convert_from_list(list_file, output_dir):
-    # 创建输出目录，如果它不存在的话
-    if not os.path.exists(output_dir):
-        os.makedirs(output_dir)
-
-    # 解析.list文件，并操作文件
-    with open(list_file, 'r', encoding='utf-8') as file:
-        lines = file.readlines()
-
-    for line in lines:
-        parts = line.strip().split('|')
-        if len(parts) != 4:
-            print(f"Line format incorrect: {line}")
-            continue
-
-        audio_path, _, _, transcription = parts
-
-        # 构建新的文件名和路径
-        new_filename = transcription + '.wav'
-        # new_filename = new_filename.replace(' ', '_')  # 移除空格
-        # new_filename = ''.join(e for e in new_filename if e.isalnum() or e in ['_', '.'])  # 移除非法字符
-        new_path = os.path.join(output_dir, new_filename)
-
-        # 如果目标文件已存在，不要覆盖
-        if os.path.exists(new_path):
-            print(f"File already exists: {new_path}")
-            continue
-
-        try:
-            # 检查音频文件是否存在
-            if not os.path.exists(audio_path):
-                print(f"Audio file does not exist: {audio_path}")
-                continue
-
-            # 复制音频文件到output目录并重命名
-            shutil.copy2(audio_path, new_path)
-            print(f"File copied and renamed to: {new_path}")
-        except Exception as e:
-            print(f"An error occurred while processing: {audio_path}")
-            print(e)
-
-    print("Processing complete.")
diff --git a/tools/speaker_verification/__init__.py b/tools/speaker_verification/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tools/speaker_verification/audio_similarity.py b/tools/speaker_verification/audio_similarity.py
new file mode 100644
index 0000000..c1f415e
--- /dev/null
+++ b/tools/speaker_verification/audio_similarity.py
@@ -0,0 +1,64 @@
+import argparse
+import os
+
+from modelscope.pipelines import pipeline
+sv_pipeline = pipeline(
+    task='speaker-verification',
+    model='/tools/speaker_verification/models/speech_campplus_sv_zh-cn_16k-common',
+    model_revision='v1.0.0'
+)
+
+
+def compare_audio_and_generate_report(reference_audio_path, comparison_dir_path, output_file_path):
+    # Step 1: 获取比较音频目录下所有音频文件的路径
+    comparison_audio_paths = [os.path.join(comparison_dir_path, f) for f in os.listdir(comparison_dir_path) if f.endswith('.wav')]
+
+    # Step 2: 用参考音频依次比较音频目录下的每个音频，获取相似度分数及对应路径
+    similarity_scores = []
+    for audio_path in comparison_audio_paths:
+        score = sv_pipeline([reference_audio_path, audio_path])['score']
+        similarity_scores.append({
+            'score': score,
+            'path': audio_path
+        })
+
+    # Step 3: 根据相似度分数降序排列
+    similarity_scores.sort(key=lambda x: x['score'], reverse=True)
+
+    # Step 4: 处理输出文件不存在的情况，创建新文件
+    if not os.path.exists(output_file_path):
+        open(output_file_path, 'w').close()  # Create an empty file
+
+    # Step 5: 将排序后的结果写入输出结果文件（支持中文）
+    formatted_scores  = [f'{item["score"]}|{item["path"]}' for item in similarity_scores]
+    with open(output_file_path, 'w', encoding='utf-8') as f:
+        # 使用'\n'将每个字符串分开，使其写入不同行
+        content = '\n'.join(formatted_scores )
+        f.write(content)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Audio processing script arguments")
+
+    # Reference audio path
+    parser.add_argument("-r", "--reference_audio", type=str, required=True,
+                        help="Path to the reference WAV file.")
+
+    # Comparison directory path
+    parser.add_argument("-c", "--comparison_dir", type=str, required=True,
+                        help="Path to the directory containing comparison WAV files.")
+
+    # Output file path
+    parser.add_argument("-o", "--output_file", type=str, required=True,
+                        help="Path to the output file where results will be written.")
+
+    return parser.parse_args()
+
+
+if __name__ == '__main__':
+    cmd = parse_arguments()
+    compare_audio_and_generate_report(
+        reference_audio_path  = cmd.reference_audio,
+        comparison_dir = cmd.comparison_dir,
+        output_file    = cmd.output_file,
+    )
\ No newline at end of file