Abstract: In general, the disclosure describes techniques for automatically generating summaries of meetings. A computing system obtains a transcript of a meeting and may produce, based on the transcript of the meeting, a data structure that comprises utterance features. Furthermore, the computing system may determine, based on the transcript of the meeting, temporal bounds of a plurality of activity episodes within the meeting. For each respective activity episode of a plurality of activity episodes, the computing system may determine, based on the utterance features associated with the respective activity episode, a conversational activity type associated with the respective activity episode. Additionally, the computing system may produce an episode summary for the respective activity episode that is dependent on the determined conversational activity type associated with the respective activity episode.

Abstract: Disclosed techniques can generate content object summaries. Content of a content object can be parsed into a set of word groups. For each word group, at least one topic to which the word group pertains can be identified and it can be determined, via a user model, at least one weight of the plurality of weights corresponding to the topic(s). For each word group, a score can be determined for the word group based on the weight(s). A subset of the set of word groups can be selected based on the scores for the word group. A summary of the content object can be generated that includes the subset but that does not include one or more other word groups in the set of word groups that are not in the subset. At least part of the summary of the content object can be output.

Abstract: In general, the disclosure describes techniques for automatically generating summaries of meetings. A computing system obtains a transcript of a meeting and may produce, based on the transcript of the meeting, a data structure that comprises utterance features. Furthermore, the computing system may determine, based on the transcript of the meeting, temporal bounds of a plurality of activity episodes within the meeting. For each respective activity episode of a plurality of activity episodes, the computing system may determine, based on the utterance features associated with the respective activity episode, a conversational activity type associated with the respective activity episode. Additionally, the computing system may produce an episode summary for the respective activity episode that is dependent on the determined conversational activity type associated with the respective activity episode.

Abstract: Disclosed techniques can generate content object summaries. Content of a content object can be parsed into a set of word groups. For each word group, at least one topic to which the word group pertains can be identified and it can be determined, via a user model, at least one weight of the plurality of weights corresponding to the topic(s). For each word group, a score can be determined for the word group based on the weight(s). A subset of the set of word groups can be selected based on the scores for the word group. A summary of the content object can be generated that includes the subset but that does not include one or more other word groups in the set of word groups that are not in the subset. At least part of the summary of the content object can be output.