Patent ID: 11967308
Assignee: SAMSUNG ELECTRONICS CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. A method of controlling an automatic speech recognition (ASR) model and a language model by an electronic device, the language model includes an input embedding layer, a positional encoding layer, at least one subnetwork layer, a linearization layer, and a softmax layer, wherein the at least one sub-network layer includes a linear normalization layer, a multi-head attention layer, a first layer including a plurality of first adapter modules respectively corresponding to different domains included in the language model, a feed-forward layer, and a second layer including a plurality of second adapter modules respectively corresponding to the different domains in the language model, wherein the different domains correspond to different contacts on a contact list or correspond to different applications, the method comprising:
entering data into the language model and generating an embedding vector based on the data in the input embedding layer;
adding position information to the embedding vector in the position encoding layer;
branching the embedding vector based on domain information included in the embedding vector, normalizing the branched embedding vectors using the linear normalization layer, and entering the normalized embedding vectors into the multi-head attention layer;
branching output data of the multi-head attention layer into one or more of the plurality of the first adapter modules of the first layer corresponding to the domain information included in the embedding vector and normalizing pieces of output data of the first layer;
entering the normalized pieces of output data of the first layer into the feed-forward layer;
branching output data of the feed-forward layer into one or more of the plurality of second adapter modules of the second layer co responding to the domain information included in the embedding vector and normalizing pieces of output data of the second layer; and
entering the normalized pieces of output data of the second layer into a linearization layer and a softmax layer to obtain result data.