A voice interaction system that is configured to have a conversation with a user by using a voice, comprising: a speech acquisition unit configured to acquire user speech given by the user; a feature extraction unit configured to extract at least a feature of the acquired user speech; a response determination unit configured to determine a response in accordance with the extracted feature using any one of a plurality of learning models generated in advance by machine learning, wherein the response is one of: silent, nod and speak; a response execution unit configured to perform control in order to execute the determined response; a user state detection unit configured to detect a user state, which is a state of the user, wherein the user state is a degree of activeness of the user in the conversation; and a learning model selection unit configured to select the learning model from the plurality of learning models in accordance with the detected user state, wherein the response determination unit is configured to determine the response using the learning model selected by the learning model selection unit, the user state detection unit is configured to detect the degree of activeness of the user in the conversation as the user state, wherein the degree of activeness is determined by detecting the percentage of the time during which the user has made a speech with respect to the sum of the time during which the voice interaction system has output a voice as a response and the time during which the user has made a speech in a predetermined period, and the learning model selection unit is configured to select the learning model that corresponds to the detected degree of activeness that corresponds to the percentage of the time during which the user has made a speech. a speech acquisition unit configured to acquire user speech given by the user; a feature extraction unit configured to extract at least a feature of the acquired user speech; a response determination unit configured to determine a response in accordance with the extracted feature using any one of a plurality of learning models generated in advance by machine learning, wherein the response is one of: silent, nod and speak; a response execution unit configured to perform control in order to execute the determined response; a user state detection unit configured to detect a user state, which is a state of the user, wherein the user state is a degree of activeness of the user in the conversation; and a learning model selection unit configured to select the learning model from the plurality of learning models in accordance with the detected user state, wherein the response determination unit is configured to determine the response using the learning model selected by the learning model selection unit, the user state detection unit is configured to detect the degree of activeness of the user in the conversation as the user state, wherein the degree of activeness is determined by detecting the percentage of the time during which the user has made a speech with respect to the sum of the time during which the voice interaction system has output a voice as a response and the time during which the user has made a speech in a predetermined period, and the learning model selection unit is configured to select the learning model that corresponds to the detected degree of activeness that corresponds to the percentage of the time during which the user has made a speech. the response determination unit is configured to determine the response using the learning model selected by the learning model selection unit, the user state detection unit is configured to detect the degree of activeness of the user in the conversation as the user state, wherein the degree of activeness is determined by detecting the percentage of the time during which the user has made a speech with respect to the sum of the time during which the voice interaction system has output a voice as a response and the time during which the user has made a speech in a predetermined period, and the learning model selection unit is configured to select the learning model that corresponds to the detected degree of activeness that corresponds to the percentage of the time during which the user has made a speech.