Abstract: The present disclosure provides computer-implemented systems and processes for augmenting user ratings of items, such as a rating of a song playing on a user device, by analyzing contextual information, such as user and/or device activity data associated with the device. The contextual information may be used to determine an associated intensity of the rating or feedback. The determined intensity levels can be used to weigh the associated rating events and improve the quality of item recommendations that are based on such ratings. Contextual information may indicate whether the user transitioned from another application to rate an item, device status information, and so on. In one embodiment, contextual information can be used to assess how intensely the user feels about a music item and to provide improved music recommendations, such as songs to provide in a playlist or radio station, based on the intensity.

Abstract: A technology for propagating themes is provided. In one example, a method may include identifying media having a content feature contained in a presentation of the media. The method may include extracting the content feature of the media as a continuous variable and discretizing the continuous variable into a bucket representing a discrete value. A theme label may be applied to the media and may be propagated to other media with continuous variables discretized into the subset of buckets.

Abstract: The present disclosure provides computer-implemented systems and processes for augmenting user ratings of items, such as a rating of a song playing on a user device, by analyzing contextual information, such as user and/or device activity data associated with the device. The contextual information may be used to determine an associated intensity of the rating or feedback. The determined intensity levels can be used to weigh the associated rating events and improve the quality of item recommendations that are based on such ratings. Contextual information may indicate whether the user transitioned from another application to rate an item, device status information, and so on. In one embodiment, contextual information can be used to assess how intensely the user feels about a music item and to provide improved music recommendations, such as songs to provide in a playlist or radio station, based on the intensity.

Abstract: A computing device can periodically acquire a current track time for a media content item being played. The device can periodically compare the current track time with a respective start time and a respective end time for each line (or segment) in a plurality of lines of text (or segments of text) associated with the media content item. If the device determines that the current track time is between start and end times for a given line of text, then the device can display the given line of text. A user of the device can scroll through the lines of text associated with the media content item. If the user selects a particular line of text, the device can identify a start time for the selected line of text. The device can then play the media content item at the identified start time of the selected line of text.

Abstract: A technology for synchronizing text with audio includes analyzing the audio to identify voice segments in the audio where a human voice is present and to identify non-voice segments in proximity to the voice segments. Segmented text associated with the audio, having text segments, may be identified and synchronized to the voice segments.

Abstract: A technology for synchronizing text with audio includes analyzing the audio to identify voice segments in the audio where a human voice is present and to identify non-voice segments in proximity to the voice segments. Segmented text associated with the audio, having text segments, may be identified and synchronized to the voice segments.

Abstract: Techniques are described for automatically selecting musical content for playback based on an initial “seed” of music selected by a user in a way that seamlessly extends the user's listening experience. The initially selected seed music might be, for example, an album or a playlist. Music that follows the seed music is algorithmically selected to match the music selected by the user.

Abstract: A computing device can periodically acquire a current track time for a media content item being played. The device can periodically compare the current track time with a respective start time and a respective end time for each line (or segment) in a plurality of lines of text (or segments of text) associated with the media content item. If the device determines that the current track time is between start and end times for a given line of text, then the device can display the given line of text. A user of the device can scroll through the lines of text associated with the media content item. If the user selects a particular line of text, the device can identify a start time for the selected line of text. The device can then play the media content item at the identified start time of the selected line of text.

Abstract: A computing device can periodically acquire a current track time for a media content item being played. The device can periodically compare the current track time with a respective start time and a respective end time for each line (or segment) in a plurality of lines of text (or segments of text) associated with the media content item. If the device determines that the current track time is between start and end times for a given line of text, then the device can display the given line of text. A user of the device can scroll through the lines of text associated with the media content item. If the user selects a particular line of text, the device can identify a start time for the selected line of text. The device can then play the media content item at the identified start time of the selected line of text.