A method implemented by one or more processors, the method comprising: receiving user input, wherein the user input is provided by a user at an automated assistant interface of a client device, and wherein the automated assistant interface is an interface for interacting with an automated assistant executing on the client device and/or one or more remote computing devices; processing the user input to determine at least one intent associated with the user input; the method being characterised by further comprising: generating a familiarity measure for the at least one intent, wherein generating the familiarity measure for the at least one intent comprises: processing, using a machine learning model, a plurality of parameters to generate the familiarity measure, wherein the plurality of parameters processed using the machine learning model to generate the familiarity measure include one or more intent specific parameters that are based on historical interactions, of the user with the automated assistant, for the at least one intent specified by the user input; determining a response, of the automated assistant to the user input, based on the familiarity measure and based on the at least one intent, wherein determining the response comprises: determining an initial response based on the determined intent, wherein the initial response comprises a first quantity of bytes: responsive to determining the familiarity measure satisfies a threshold: modifying the initial response to generate the abridged response, wherein the abridged response comprises a second quantity of bytes that is less than the first quantity of bytes; and causing the client device to render the determined response. receiving user input, wherein the user input is provided by a user at an automated assistant interface of a client device, and wherein the automated assistant interface is an interface for interacting with an automated assistant executing on the client device and/or one or more remote computing devices; processing the user input to determine at least one intent associated with the user input; the method being characterised by further comprising: generating a familiarity measure for the at least one intent, wherein generating the familiarity measure for the at least one intent comprises: processing, using a machine learning model, a plurality of parameters to generate the familiarity measure, wherein the plurality of parameters processed using the machine learning model to generate the familiarity measure include one or more intent specific parameters that are based on historical interactions, of the user with the automated assistant, for the at least one intent specified by the user input; determining a response, of the automated assistant to the user input, based on the familiarity measure and based on the at least one intent, wherein determining the response comprises: determining an initial response based on the determined intent, wherein the initial response comprises a first quantity of bytes: responsive to determining the familiarity measure satisfies a threshold: modifying the initial response to generate the abridged response, wherein the abridged response comprises a second quantity of bytes that is less than the first quantity of bytes; and causing the client device to render the determined response. generating a familiarity measure for the at least one intent, wherein generating the familiarity measure for the at least one intent comprises: processing, using a machine learning model, a plurality of parameters to generate the familiarity measure, wherein the plurality of parameters processed using the machine learning model to generate the familiarity measure include one or more intent specific parameters that are based on historical interactions, of the user with the automated assistant, for the at least one intent specified by the user input; determining a response, of the automated assistant to the user input, based on the familiarity measure and based on the at least one intent, wherein determining the response comprises: determining an initial response based on the determined intent, wherein the initial response comprises a first quantity of bytes: responsive to determining the familiarity measure satisfies a threshold: modifying the initial response to generate the abridged response, wherein the abridged response comprises a second quantity of bytes that is less than the first quantity of bytes; and processing, using a machine learning model, a plurality of parameters to generate the familiarity measure, wherein the plurality of parameters processed using the machine learning model to generate the familiarity measure include one or more intent specific parameters that are based on historical interactions, of the user with the automated assistant, for the at least one intent specified by the user input; determining a response, of the automated assistant to the user input, based on the familiarity measure and based on the at least one intent, wherein determining the response comprises: determining an initial response based on the determined intent, wherein the initial response comprises a first quantity of bytes: responsive to determining the familiarity measure satisfies a threshold: modifying the initial response to generate the abridged response, wherein the abridged response comprises a second quantity of bytes that is less than the first quantity of bytes; and causing the client device to render the determined response.