An information processing device, comprising: learning means for extracting an image feature amount of each frame of an image of learning content and extracting word frequency information regarding a frequency of appearance of each word in a description text describing a content of the image of the learning content as a text feature amount of the description text, and learning an annotation model, which is a multi-stream HMM (hidden Markov model), by using an annotation sequence for annotation, which is a multi-stream including the image feature amount and the text feature amount; and browsing controlling means for extracting a scene, which is a group of one or more temporally continuous frames, from target content from which the scene is to be extracted by using the annotation model, and displaying representative images of scenes so as to be arranged in chronological order, wherein the learning content includes a text of a caption, and the description text is the text of the caption included in the learning content; and the learning means extracts words included in the text of the caption displayed in a window as one document while shifting the window of a predetermined time length at regular intervals, and extracts multinomial distribution, which represents a frequency of appearance of each word in the document, as the text feature amount, and the browsing controlling means extracts the image feature amount of each frame of the image of the target content and composes the annotation sequence by using the image feature amount, obtains a maximum likelihood state sequence in which the annotation sequence is observed in the annotation model, selects a word with high frequency in the multinomial distribution observed in a state corresponding to a noted frame of interest out of states of the maximum likelihood state sequence as an annotation to be added to the frame of interest, extracts a group of one or more temporally continuous frames to which the same annotation is added as the scene from the target content, and displays the representative images of the scenes so as to be arranged in chronological order. learning means for extracting an image feature amount of each frame of an image of learning content and extracting word frequency information regarding a frequency of appearance of each word in a description text describing a content of the image of the learning content as a text feature amount of the description text, and learning an annotation model, which is a multi-stream HMM (hidden Markov model), by using an annotation sequence for annotation, which is a multi-stream including the image feature amount and the text feature amount; and browsing controlling means for extracting a scene, which is a group of one or more temporally continuous frames, from target content from which the scene is to be extracted by using the annotation model, and displaying representative images of scenes so as to be arranged in chronological order, wherein the learning content includes a text of a caption, and the description text is the text of the caption included in the learning content; and the learning means extracts words included in the text of the caption displayed in a window as one document while shifting the window of a predetermined time length at regular intervals, and extracts multinomial distribution, which represents a frequency of appearance of each word in the document, as the text feature amount, and the browsing controlling means extracts the image feature amount of each frame of the image of the target content and composes the annotation sequence by using the image feature amount, obtains a maximum likelihood state sequence in which the annotation sequence is observed in the annotation model, selects a word with high frequency in the multinomial distribution observed in a state corresponding to a noted frame of interest out of states of the maximum likelihood state sequence as an annotation to be added to the frame of interest, extracts a group of one or more temporally continuous frames to which the same annotation is added as the scene from the target content, and displays the representative images of the scenes so as to be arranged in chronological order.