AI与电影翻译：机器学习字幕的链上版权管理

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;

import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
import "@openzeppelin/contracts/access/Ownable.sol";

contract AISubtitleCopyright is ERC721, Ownable {
    struct Subtitle {
        uint256 id;
        string movieTitle;
        string sourceLanguage;
        string targetLanguage;
        string aiModel;
        bytes32 contentHash;
        address translator;
        uint256 qualityScore;
        uint256 timestamp;
        bool isVerified;
        uint256 usageCount;
    }
    
    struct TranslationJob {
        uint256 jobId;
        uint256 subtitleId;
        address client;
        uint256 fee;
        uint256 deadline;
        bool isCompleted;
    }
    
    mapping(uint256 => Subtitle) public subtitles;
    mapping(uint256 => TranslationJob) public jobs;
    mapping(address => uint256) public translatorReputation;
    
    uint256 public subtitleCount;
    uint256 public jobCount;
    
    event SubtitleRegistered(uint256 indexed id, string movieTitle, string targetLanguage);
    event TranslationJobCreated(uint256 indexed jobId, uint256 indexed subtitleId);
    event QualityVerified(uint256 indexed subtitleId, uint256 score);
    
    constructor() ERC721("AISubtitle", "ASUB") {}
    
    function registerSubtitle(
        string memory _movieTitle,
        string memory _sourceLanguage,
        string memory _targetLanguage,
        string memory _aiModel,
        bytes32 _contentHash
    ) external returns (uint256) {
        subtitleCount++;
        subtitles[subtitleCount] = Subtitle({
            id: subtitleCount,
            movieTitle: _movieTitle,
            sourceLanguage: _sourceLanguage,
            targetLanguage: _targetLanguage,
            aiModel: _aiModel,
            contentHash: _contentHash,
            translator: msg.sender,
            qualityScore: 0,
            timestamp: block.timestamp,
            isVerified: false,
            usageCount: 0
        });
        
        _safeMint(msg.sender, subtitleCount);
        emit SubtitleRegistered(subtitleCount, _movieTitle, _targetLanguage);
        return subtitleCount;
    }
    
    function createTranslationJob(
        uint256 _subtitleId,
        uint256 _fee,
        uint256 _deadlineDays
    ) external payable {
        require(msg.value >= _fee, "Insufficient fee");
        
        jobCount++;
        jobs[jobCount] = TranslationJob({
            jobId: jobCount,
            subtitleId: _subtitleId,
            client: msg.sender,
            fee: _fee,
            deadline: block.timestamp + (_deadlineDays * 1 days),
            isCompleted: false
        });
        
        emit TranslationJobCreated(jobCount, _subtitleId);
    }
    
    function verifyQuality(uint256 _subtitleId, uint256 _score) external {
        Subtitle storage sub = subtitles[_subtitleId];
        sub.qualityScore = _score;
        sub.isVerified = true;
        
        translatorReputation[sub.translator] += _score;
        
        emit QualityVerified(_subtitleId, _score);
    }
}

import numpy as np
import pandas as pd
from typing import Dict, List
import matplotlib.pyplot as plt

class TranslationAnalyzer:
    def __init__(self):
        self.translations = []
        
    def generate_synthetic_data(self, n: int = 100):
        np.random.seed(42)
        languages = ['中文', '英文', '日文', '韩文', '法文', '德文', '西班牙文']
        models = ['GPT-4', 'Claude', 'Gemini', 'DeepL', 'Custom']
        
        for i in range(n):
            translation = {
                'id': i + 1,
                'source': np.random.choice(languages),
                'target': np.random.choice(languages),
                'model': np.random.choice(models),
                'quality_score': np.random.uniform(60, 100),
                'speed': np.random.uniform(0.1, 5),
                'cost': np.random.uniform(0.01, 0.5),
                'is_ai_generated': np.random.random() > 0.3
            }
            self.translations.append(translation)
    
    def analyze_quality(self) -> Dict:
        df = pd.DataFrame(self.translations)
        ai_df = df[df['is_ai_generated']]
        human_df = df[~df['is_ai_generated']]
        
        return {
            'ai_avg_quality': ai_df['quality_score'].mean(),
            'human_avg_quality': human_df['quality_score'].mean(),
            'ai_avg_speed': ai_df['speed'].mean(),
            'human_avg_speed': human_df['speed'].mean(),
            'ai_avg_cost': ai_df['cost'].mean(),
            'human_avg_cost': human_df['cost'].mean(),
            'best_model': df.groupby('model')['quality_score'].mean().idxmax()
        }
    
    def generate_report(self) -> str:
        eff = self.analyze_quality()
        report = f"""
=== AI翻译质量分析 ===

AI平均质量: {eff['ai_avg_quality']:.1f}
人工平均质量: {eff['human_avg_quality']:.1f}
AI平均速度: {eff['ai_avg_speed']:.2f} 秒/句
人工平均速度: {eff['human_avg_speed']:.2f} 秒/句
AI平均成本: ${eff['ai_avg_cost']:.3f}
人工平均成本: ${eff['human_avg_cost']:.3f}
最佳模型: {eff['best_model']}
"""
        return report


if __name__ == "__main__":
    analyzer = TranslationAnalyzer()
    analyzer.generate_synthetic_data(100)
    report = analyzer.generate_report()
    print(report)

class SubtitleManager {
    constructor(providerUrl, contractAddress) {
        this.web3 = new Web3(providerUrl);
        this.contract = new this.web3.eth.Contract([], contractAddress);
    }
    
    async registerSubtitle(movieTitle, sourceLang, targetLang, aiModel, contentHash) {
        return await this.contract.methods
            .registerSubtitle(movieTitle, sourceLang, targetLang, aiModel, contentHash)
            .send({ from: this.userAccount });
    }
    
    async createJob(subtitleId, fee, deadlineDays) {
        const feeWei = this.web3.utils.toWei(fee.toString(), 'ether');
        return await this.contract.methods
            .createTranslationJob(subtitleId, feeWei, deadlineDays)
            .send({ from: this.userAccount, value: feeWei });
    }
}

const manager = new SubtitleManager('https://mainnet.infura.io/v3/YOUR_ID', '0x...');