Disclosed herein is a denoising device including a deriving part configured to, when corrupted noise data corrupted due to noises is received from source data, derive an estimated loss which is estimated when each symbol within noise data is reconstructed to the source data based on a predefined noise occurrence probability, a processor to process training of a defined learning model by including parameters related with the reconstruction of the source data from the noise data based on context composed of a sequence of neighbored symbols based on each symbol within the noise data and pseudo-training data using the estimated loss corresponding to the context, and an output part to output reconstructed data in which each symbol within the noise data is reconstructed to a symbol of the source data through a denoiser formed based on a result of the training processing.