1. A method for determining parameters of a hidden Markov model (HMM) stored at a server based on an observation sequence stored at a client, wherein the client has a decryption key and an encryption key of an additively homomorphic cryptosystem, and the server has only the encryption key, comprising the steps of initializing parameters of the HMM; determining an encryption of a probability of the observation sequence with respect to the parameters of the HMM using an H-SMC, wherein the H-SMC includes a secure multiparty computation (SMC) between the server and the client using at least one property of additive homomorphism; determining, for each state of the HMM, an encrypted forward probability of the observation sequence with respect to the parameters of the HMM using the SMC; deter mining, for each state of the HMM, an encrypted backward probability of the observation sequence using the H-SMC; determining, for each element of the observation sequence, an encrypted conditional joint probability of each pair of states given the parameters of the HMM to produce a set of encrypted conditional joint probabilities, wherein the determining is based on the encryption of the log-probability of the observation sequence, the encrypted forward probability, and the encrypted backward probability, wherein the deter mining is performed in encrypted domain using at least one property of additive homomorphism; and updating, using the H-SMC having as input the set of encrypted conditional joint probabilities, the parameters of the HMM, wherein steps of the method are performed by the server.