Abstract: Embodiments are direct to methods and systems for authenticating a user and interpolating user preference embeddings. The systems generate, using a neural network trained to generate features based on training data comprising human voices spoken by a plurality of historical speakers inside a vehicle, input features based on a human voice of a current speaker inside the vehicle, and calculates similarities between an input vector of the input features and historical vectors in voiceprints of one or more enrolled users. After determining a similarity between the input vector and at least one historical vector in a voiceprint of an identified user is less than a threshold similarity, the systems authenticate the current speaker as the identified user, calculate a probabilistic notion based on the similarity, and apply the probabilistic notion to interpolate between downstream user preference embeddings associated with the identified user.