Method and device for recognition and method and device for constructing recognition model

A method of constructing a recognition model, the method comprising:

• obtaining a first recognition model trained based on basic training data;
• obtaining new additional training data separate from the basic training data;
• generating a second recognition model by further training, using one or more hardware processors, the first recognition model to learn the additional training data;
• and
• constructing, using the one or more hardware processors, a final recognition model by integrating the first recognition model with the second recognition model,
• wherein, in the integrating of the first recognition model with the second recognition model a select weight of the second recognition model is set to emphasize learning of the additional training data over maintaining of the first recognition model, or is set to emphasize the maintaining of the first recognition model over the learning of the additional training data.

A recognition device comprising:

• one or more hardware processors configured to:
• receive data to be recognized from a user;
• determine, based on the received data, whether to update a recognition model constructed in advance based on basic training data;
• in response to a determination that an update is required, train the recognition model to learn new additional training data separate from the basic training data to update the recognition model, the updating of the recognition model being performed to emphasize learning of the received data over maintaining of the recognition model, or performed to emphasize the maintaining of the recognition model over the learning of the received data;
• and
• recognize the received data using the recognition model constructed in advance or the updated recognition model.

A recognition model construction device, comprising:

• one or more hardware processors configured to:
• obtain a first recognition model trained based on basic training data;
• obtain a second recognition model by training the first recognition model to learn new additional training data separate from the basic training data;
• and
• construct a third recognition model by integrating the first recognition model with the second recognition model based on a select weight, the select weight being set to emphasize learning of the additional training data over maintaining of the first recognition model, or is set to emphasize the maintaining of the first recognition model over the learning of the additional training data.