1. A keyword detector comprising: a processor configured to: divide a speech signal into frames each with a predetermined time length; calculate a feature vector including a plurality of features representing characteristics of a human voice, for each frame; input the feature vector for each of the frames to a deep neural network to calculate a first output probability for each of a plurality of triphones according to a sequence of phonemes contained in a predetermined keyword, for each of at least one state of a Hidden Markov Model and calculate a second output probability for each of a plurality of monophones, for each of at least one state of the Hidden Markov Model; calculate a first likelihood representing a probability that the predetermined keyword is uttered in the speech signal by applying the first output probability to the Hidden Markov Model; calculate a second likelihood for a most probable phoneme string in the speech signal by applying the second output probability to the Hidden Markov Model; and determine whether the keyword is to be detected on the basis of the first likelihood and the second likelihood.