3. The learning device according to claim 1 , wherein the pattern learning model is an HMM, an RNN, an FNN, an SVR or an RNNPB.
1. A learning device comprising: a processor and at least one non-transitory computer readable medium encoded with program instructions; a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing unit that causes, using the processor, two or more learning modules from among the plurality of learning modules to share the model parameters; and classification unit that classifies the plurality of learning modules on the basis of the plurality of model parameters of each of the learning modules after the update learning, wherein the model parameter sharing unit corrects the model parameters updated by each of the two or more learning modules using a weight average value of the model parameters updated respectively by the two or more learning modules to thereby cause the two or more learning modules to share the model parameters updated respectively by the two or more learning modules.