Viterbi decoder and speech recognition method using same

A speech recognition method using a Viterbi decoder, the method comprising:

• generating an observation vector sequence by converting an input speech to a sequence of observation vectors;
• obtaining, among states constituting a hidden Markov model, a partial state sequence having a maximum similarity up to a current observation vector as an optimal state;
• obtaining, as a current observation probability, a probability for observing the current observation vector in the optimal state;
• calculating a filtered probability by using previous observation probabilities and the current observation probability;
• calculating a partial maximum likelihood by using the filtered probability;
• updating a cumulative maximum likelihood by using the partial maximum likelihood;
• and
• outputting a recognition result for the input speech based on the cumulative maximum likelihood,
• wherein said obtaining the optimal state, said obtaining the current observation probability, said calculating the filtered probability, said calculating the partial maximum likelihood and said updating the cumulative maximum likelihood are repeated until it reaches the last observation vector in the observation vector sequence.