219 lines
7.4 KiB
Python
219 lines
7.4 KiB
Python
"""
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声纹服务 - 处理用户声纹采集、存储和验证
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"""
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import os
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import json
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import wave
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from datetime import datetime
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from typing import Optional, Dict
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from pathlib import Path
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from app.core.database import get_db_connection
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import app.core.config as config_module
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class VoiceprintService:
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"""声纹服务类 - 同步处理声纹采集"""
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def __init__(self):
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self.voiceprint_dir = config_module.VOICEPRINT_DIR
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self.voiceprint_config = config_module.VOICEPRINT_CONFIG
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def get_user_voiceprint_status(self, user_id: int) -> Dict:
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"""
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获取用户声纹状态
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Args:
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user_id: 用户ID
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Returns:
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Dict: 声纹状态信息
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"""
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try:
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with get_db_connection() as connection:
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cursor = connection.cursor(dictionary=True)
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query = """
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SELECT vp_id, user_id, file_path, file_size, duration_seconds, collected_at, updated_at
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FROM user_voiceprint
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WHERE user_id = %s
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"""
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cursor.execute(query, (user_id,))
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voiceprint = cursor.fetchone()
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if voiceprint:
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return {
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"has_voiceprint": True,
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"vp_id": voiceprint['vp_id'],
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"file_path": voiceprint['file_path'],
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"duration_seconds": float(voiceprint['duration_seconds']) if voiceprint['duration_seconds'] else None,
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"collected_at": voiceprint['collected_at'].isoformat() if voiceprint['collected_at'] else None
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}
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else:
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return {
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"has_voiceprint": False,
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"vp_id": None,
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"file_path": None,
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"duration_seconds": None,
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"collected_at": None
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}
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except Exception as e:
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print(f"获取声纹状态错误: {e}")
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raise e
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def save_voiceprint(self, user_id: int, audio_file_path: str, file_size: int) -> Dict:
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"""
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保存声纹文件并提取特征向量
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Args:
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user_id: 用户ID
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audio_file_path: 音频文件路径
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file_size: 文件大小
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Returns:
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Dict: 保存结果
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"""
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try:
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# 1. 获取音频时长
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duration = self._get_audio_duration(audio_file_path)
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# 2. 提取声纹向量（调用FunASR）
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vector_data = self._extract_voiceprint_vector(audio_file_path)
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# 3. 保存到数据库
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with get_db_connection() as connection:
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cursor = connection.cursor(dictionary=True)
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# 检查用户是否已有声纹
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cursor.execute("SELECT vp_id FROM user_voiceprint WHERE user_id = %s", (user_id,))
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existing = cursor.fetchone()
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# 计算相对路径
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relative_path = str(Path(audio_file_path).relative_to(config_module.BASE_DIR))
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if existing:
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# 更新现有记录
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update_query = """
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UPDATE user_voiceprint
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SET file_path = %s, file_size = %s, duration_seconds = %s,
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vector_data = %s, updated_at = NOW()
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WHERE user_id = %s
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"""
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cursor.execute(update_query, (
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relative_path, file_size, duration,
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json.dumps(vector_data) if vector_data else None,
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user_id
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))
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vp_id = existing['vp_id']
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else:
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# 插入新记录
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insert_query = """
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INSERT INTO user_voiceprint
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(user_id, file_path, file_size, duration_seconds, vector_data, collected_at, updated_at)
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VALUES (%s, %s, %s, %s, %s, NOW(), NOW())
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"""
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cursor.execute(insert_query, (
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user_id, relative_path, file_size, duration,
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json.dumps(vector_data) if vector_data else None
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))
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vp_id = cursor.lastrowid
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connection.commit()
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return {
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"vp_id": vp_id,
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"user_id": user_id,
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"file_path": relative_path,
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"file_size": file_size,
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"duration_seconds": duration,
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"has_vector": vector_data is not None
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}
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except Exception as e:
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print(f"保存声纹错误: {e}")
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raise e
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def delete_voiceprint(self, user_id: int) -> bool:
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"""
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删除用户声纹
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Args:
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user_id: 用户ID
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Returns:
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bool: 是否删除成功
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"""
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try:
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with get_db_connection() as connection:
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cursor = connection.cursor(dictionary=True)
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# 获取文件路径
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cursor.execute("SELECT file_path FROM user_voiceprint WHERE user_id = %s", (user_id,))
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voiceprint = cursor.fetchone()
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if voiceprint:
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# 构建完整文件路径
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relative_path = voiceprint['file_path']
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if relative_path.startswith('/'):
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relative_path = relative_path.lstrip('/')
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file_path = config_module.BASE_DIR / relative_path
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# 删除数据库记录
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cursor.execute("DELETE FROM user_voiceprint WHERE user_id = %s", (user_id,))
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connection.commit()
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# 删除文件
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if file_path.exists():
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os.remove(file_path)
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return True
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else:
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return False
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except Exception as e:
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print(f"删除声纹错误: {e}")
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raise e
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def _get_audio_duration(self, audio_file_path: str) -> float:
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"""
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获取音频文件时长
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Args:
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audio_file_path: 音频文件路径
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Returns:
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float: 时长（秒）
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"""
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try:
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with wave.open(audio_file_path, 'rb') as wav_file:
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frames = wav_file.getnframes()
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rate = wav_file.getframerate()
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duration = frames / float(rate)
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return round(duration, 2)
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except Exception as e:
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print(f"获取音频时长错误: {e}")
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return 10.0 # 默认返回10秒
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def _extract_voiceprint_vector(self, audio_file_path: str) -> Optional[list]:
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"""
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提取声纹特征向量（调用FunASR）
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Args:
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audio_file_path: 音频文件路径
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Returns:
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Optional[list]: 声纹向量（192维），失败返回None
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"""
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# TODO: 集成FunASR的说话人识别模型
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# 使用 speech_campplus_sv_zh-cn_16k-common 模型
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# 返回192维的embedding向量
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print(f"[TODO] 调用FunASR提取声纹向量: {audio_file_path}")
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# 暂时返回None，等待FunASR集成
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# 集成后应该返回类似: [0.123, -0.456, 0.789, ...]
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return None
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# 创建全局实例
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voiceprint_service = VoiceprintService()
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