A speech dereverberation apparatus that outputs a dereverberated signal obtained by cancelling reverberation due to room acoustics from an observed signal, the speech dereverberation apparatus comprising: a likelihood maximization unit that determines a source signal estimate that maximizes a likelihood function and outputs the source signal estimate determined, as the dereverberated signal, wherein the likelihood function is defined based on a probability density function that is evaluated in accordance with an unknown parameter, a first random variable of missing data, and a second random variable of observed data, the unknown parameter representing the source signal estimate, the first random variable of missing data representing an inverse filter of a room transfer function representing dereverberation features of room acoustics, and the second random variable of observed data being defined with reference to the observed signal and an initial source signal estimate, the probability density function is divisible into an acoustics probability density function and a source probability density function, the acoustics probability density function being defined as a joint probability density function of the observed signal and the inverse filter in a case that a source signal is given, and the source probability density function being defined as a probability density function of the initial source signal estimate in the case that the source signal is given, the likelihood maximization unit calculates an inverse filter estimate with reference to the observed signal, the initial source signal estimate, and a first variance, the inverse filter estimate being an estimate of the inverse filter, and the first variance being a variance of the acoustics probability density function and representing an acoustic ambient uncertainty, the likelihood maximization unit generates a filtered signal by multiplying the observed signal by the inverse filter estimate calculated, the likelihood maximization unit generates a transformed filtered signal by performing an LTFS-to-STFS transformation of the filtered signal, and the likelihood maximization unit determines the source signal estimate by combining the transformed filtered signal and the initial source signal estimate according to a ratio defined by the first variance and a second variance, the second variance being a variance of the source probability density function and representing a source signal uncertainty. a likelihood maximization unit that determines a source signal estimate that maximizes a likelihood function and outputs the source signal estimate determined, as the dereverberated signal, wherein the likelihood function is defined based on a probability density function that is evaluated in accordance with an unknown parameter, a first random variable of missing data, and a second random variable of observed data, the unknown parameter representing the source signal estimate, the first random variable of missing data representing an inverse filter of a room transfer function representing dereverberation features of room acoustics, and the second random variable of observed data being defined with reference to the observed signal and an initial source signal estimate, the probability density function is divisible into an acoustics probability density function and a source probability density function, the acoustics probability density function being defined as a joint probability density function of the observed signal and the inverse filter in a case that a source signal is given, and the source probability density function being defined as a probability density function of the initial source signal estimate in the case that the source signal is given, the likelihood maximization unit calculates an inverse filter estimate with reference to the observed signal, the initial source signal estimate, and a first variance, the inverse filter estimate being an estimate of the inverse filter, and the first variance being a variance of the acoustics probability density function and representing an acoustic ambient uncertainty, the likelihood maximization unit generates a filtered signal by multiplying the observed signal by the inverse filter estimate calculated, the likelihood maximization unit generates a transformed filtered signal by performing an LTFS-to-STFS transformation of the filtered signal, and the likelihood maximization unit determines the source signal estimate by combining the transformed filtered signal and the initial source signal estimate according to a ratio defined by the first variance and a second variance, the second variance being a variance of the source probability density function and representing a source signal uncertainty.