我想使用带有维特比算法的隐马尔可夫模型来纠正拼写错误，我已经计算了所需的概率，但当我应用维特比算法时，得到的结果非常差，我逐行检查了代码却找不到错误
public ForwardViterbi(string[] states, string[] observations, double[] startProbability, double[,] transitionProbability, double[,] emissionProbability, double scaleFactor) { this.states = states; this.observations = observations; this.startProbability = startProbability; this.transitionProbability = transitionProbability; this.emissionProbability = emissionProbability; this.scaleFactor = scaleFactor; } //---------------------------------------------------------------------- //The Methods public void Process(int[] problem) { double[,] T = new double[states.Length, 3]; //We will store the probability sequence for the Viterbi Path vPath = new int[problem.Length]; vProbs = new double[problem.Length]; //initialize T //------------------------------------------------------------------ for (int state = 0; state < states.Length; state++) { T[state, 0] = startProbability[state]; T[state, 1] = state; T[state, 2] = startProbability[state]; } for (int output = 0; output < problem.Length; output++) { double[,] U = new double[states.Length, 3]; //We will use this array to calculate the future probabilities Console.WriteLine("\nTesting hypothesis {0} ({1})", output, observations[problem[output]]); double highest = 0; for (int nextState = 0; nextState < states.Length; nextState++) { double total = 0; double argMax = 0; double valMax = 0; Console.WriteLine(" Estimating probability for future state {0} ({1})", nextState, states[nextState]); for (int state = 0; state < states.Length; state++) { Console.WriteLine(" The testing state is {0} ({1})", states[state], state); double prob = T[state, 0]; double v_path = T[state, 1]; double v_prob = T[state, 2]; double p = emissionProbability[state, problem[output]] * transitionProbability[state, nextState] * scaleFactor; prob *= p; v_prob *= p; total += prob; if (v_prob > valMax) { valMax = v_prob; argMax = nextState; } Console.WriteLine(" VProbability of {0} is {1} with scale {2}^{3}", states[nextState], v_prob, scaleFactor, output + 1); if (v_prob > highest) { highest = v_prob; vPath[output] = nextState; vProbs[output] = v_prob; } } U[nextState, 0] = total; U[nextState, 1] = argMax; U[nextState, 2] = valMax; } T = U; Console.WriteLine("The highest probability was {0} in state {1} (scale factor of {2}^{3})", highest, states[vPath[output]], scaleFactor, output + 1); } //Apply SumMax double Total = 0; double ValMax = 0; for (int state = 0; state < states.Length; state++) { double prob = T[state, 0]; double v_path = T[state, 1]; double v_prob = T[state, 2]; Total += prob; if (v_prob > ValMax) { ValMax = v_prob; } } Console.WriteLine("\nAnalysis: Total probability (sum of all paths) for the given state is :: {0}\nThe Viterbi Path Probability is :: {1}", Total, ValMax); Console.WriteLine("The above results are presented with a scale factor of {0}^{1}", scaleFactor, problem.Length); }回答：
我刚刚检查了这个实现和维基百科上发布的那个。这个似乎不起作用。维基百科上的那个确实有效。如果你愿意 – 你可以比较它们，但我懒得做这个。
（我已经为你描述的问题实现了这里的解决方案）
