Self-training data sorting device, estimation model learning device, self-training data sorting method, estimation model learning method, and program

摘要

Self-train the estimation model using a large number of teacher-unlabeled utterances. The estimation model learning unit (11) learns an estimation model that estimates the certainty for each predetermined label from each of the features extracted from the input data, using a plurality of independent features extracted from the utterance with the teacher label. .. The paralanguage information estimation unit (12) estimates the certainty of each label using an estimation model from the features extracted from the utterance without a teacher label. The data selection unit (13) corresponds to the certainty when the certainty of each label obtained from the utterance without the teacher label exceeds all the certainty thresholds set in advance for each feature with respect to the feature amount to be learned. The label is added as a teacher label to the data without a teacher label and selected as self-training data. The estimation model re-learning unit (14) re-learns the estimation model using the self-training data.