14. A device comprising a processor and a memory; the memory configured to store samples and target values; the samples comprising temporal windows of token instances to which a user was exposed, wherein the temporal windows of token instances comprise a window comprising instantiations of first and second tokens that have overlapping instantiation periods; the samples further comprise data on previous instantiations of the first and second tokens, to which the user was exposed; and the target values correspond to the temporal windows of token instances and represent affective responses of the user to the token instances from the temporal windows of token instances; wherein the affective responses comprise at least one of: values representing emotional responses, and values of a user measurement channel of the user; the processor configured to train a machine learning-based user response model using date comprising: the samples, the data on previous instantiations of the first and second tokens, and the corresponding target values stored in the memory; and the processor is further configured to generate, based on the machine learning-based user response model, a habituation-compensated library that comprises for each token of the first and second tokens: a first expected affective response of the user to an instance of the token after a first number of previous exposures to instantiations of the token, and a second expected affective response of the user to an instance of the token after a second number, that is greater than the first number, of previous exposures to instantiations of the token; wherein for the first token, the first expected affective response is stronger than the second expected affective response, while for the second token, the first expected affective response is weaker than the second expected affective response.
15. The device of claim 14 , wherein the habituation-compensated library comprises expected emotional responses of the user to instantiations of tokens.