AI视频翻译如何做到“以假乱真”？揭秘口型同步与情感保留技术

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import cv2
import mediapipe as mp

# 初始化面部网格检测
mp_face_mesh = mp.solutions.face_mesh
face_mesh = mp_face_mesh.FaceMesh()

# 提取嘴唇关键点
def extract_lip_movements(frame):
    results = face_mesh.process(frame)
    lip_points = []
    if results.multi_face_landmarks:
        for landmark in results.multi_face_landmarks[0].landmark:
            # 提取嘴唇周围的20个关键点
            if 0 <= landmark.x <= 1 and 0 <= landmark.y <= 1:
                lip_points.append((landmark.x, landmark.y))
    return lip_points

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class PhonemeLipSync:
    def __init__(self):
        self.phoneme_to_viseme = {
            'AA': 'open_wide',    # 如"father"
            'IY': 'smile',        # 如"see"
            'UW': 'round',        # 如"too"
            'MM': 'closed',       # 如"mother"
            # ... 其他音素映射
        }
    
    def predict_viseme_sequence(self, phonemes):
        return [self.phoneme_to_viseme[p] for p in phonemes]

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class MultimodalEmotionAnalyzer:
    def analyze_emotion(self, audio, video_frames, text):
        # 语音情感分析
        audio_emotion = self.audio_analyzer(audio)
        
        # 面部表情分析
        visual_emotion = self.face_analyzer(video_frames)
        
        # 文本情感分析
        text_emotion = self.text_analyzer(text)
        
        # 多模态融合
        return self.fusion_network(
            audio_emotion, visual_emotion, text_emotion
        )