Abstract: A label collection apparatus includes an acquirer configured to acquire a teacher label of teacher data used for machine learning, a learning processor configured to execute machine learning of a model on the basis of the teacher data including the acquired teacher label, an accuracy detector configured to detect an accuracy of the model, and a presentation processor configured to present the accuracy, in which the acquirer is configured to acquire updated teacher data.

Abstract: Provided is a labeling device for teacher data used in learning during machine learning for estimating a time series of actions from data detected by a sensor. The labeling device includes a keyword extraction unit that extracts, as teacher label candidates which are candidates for teacher labels, action keywords indicating the actions included in text data in which the actions are recorded in a natural language text format; and a selection unit that selects the teacher labels corresponding to time information indicating candidates for times at which the actions are performed from the candidates for the teacher labels extracted by the keyword extraction unit.