Abstract: A system and method for providing an application programming interface for interfacing with audio files within a social networking service are provided. The method includes receiving, at the one or more computing devices, an ordered list of social networking contacts associated with a member of the social networking service. The ordered list of social networking contacts is arranged according to a ranking of the social networking contacts. The method also includes receiving a list of audio files associated with the member of the social networking service. The method also includes receiving a set of instructions. The set of instructions is configured to be implemented with the ordered list of social networking contacts and the list of audio files. The method also includes interfacing with the ordered list of social networking contacts or the list of audio files according to the set of instructions to modify the list of audio files.

Abstract: Techniques are disclosed for producing a collaborative recording of an audio event. An online server or service identifies participating mobile devices with recording capabilities that are available for recording at least a portion of the audio event. The online server or service determines the locations of the potential participating mobile devices, and identifies ranges of frequencies to be recorded by each of the participating mobile devices. The individual recordings are then compiled into a final collaborative recording.

Abstract: A system and method for recommending audio files to member of social network are provided. Method includes receiving representation of first set of audio files and representation of set of social networking contacts associated with member, and representation of one or more second sets of audio files. Each second set of audio files is associated with at least one social networking contact in set of social networking contacts associated with member. Method also includes determining first set of characteristics based on representation of first set of audio files. Method also includes determining second set of characteristics based on representation of one or more second sets of audio files. Method also includes generating recommendation for new audio file based on first set of characteristics and second set of characteristics. New audio file is not in first set of audio files. Method also includes providing indication of recommendation for new audio file.

Abstract: Sound representations and winner-take-all codes of auditory spectra are used in the identification of audio content. A transformation component converts a set of sound frames from audio content into a set of spectral slices. A spectral encoder component encodes the spectral slices of auditory spectra into winner-take-all codes with a winner-take-all hash function. An identification component identifies which spectral dimension of a subset of spectral dimensions within a spectral slice has highest spectral value according to the winner-take-all codes. Reference audio content is determined to be similar or matching to the audio content based on the winner-take-all codes.

Abstract: Method and apparatus for transparent, steerable recommendations. A steerable recommender uses tag clouds including descriptive tags and associated weights to generate recommendations. Users may dynamically interact with the recommender via a user interface to steer the recommendations. A tag cloud for an item is displayed, items for which associated tag clouds are most similar to the displayed tag cloud are identified, and the items are displayed as recommendations. The strength of similarity of the items to the displayed tag cloud may be displayed. The user may modify a tag cloud, for example by changing the weight of a tag or by adding or removing a tag, and the recommendations may be automatically updated to reflect the modification. A recommended item may be selected to display the tag cloud corresponding to the item. A user may select a user interface element to request information on why a particular item was recommended.

Abstract: An asymmetric system for obtaining recommendations is disclosed. A reference magnitude may be obtained from a seed and/or a user model. The reference magnitude may be utilized to adjust the magnitude of candidate vectors that represent one or more items in a multi-dimensional vector space. This permits an item to receive credit for a popularity up to a certain point. The dot products between the adjusted candidate vectors and the seed vector may be obtained and, in some configurations, ranked. The highest dot products may correspond to items that are preferred to be recommended according to an implementation.

Abstract: A user feedback module, executable by a processing device from memory is disclosed. The user feedback module receives from a user device a selection of a seed media item. The seed media item includes a seed label. The user feedback module further generates a list, the list includes the seed label and a set of related labels based on the seed label. The seed label and each related label include a separate label weight. The user feedback module also identifies multiple media items associated with an associate label. The associate label includes at least one of the seed label or a related label of the first set of related labels. The user feedback module also transmits to the user device a first media item from the multiple media items. The user feedback module adjusts the label weight of the associate label based on a user feedback on the first media item.

Abstract: Described herein are methods and system for analyzing music audio. An example method includes obtaining a music audio track, calculating acoustic features of the music audio track, calculating geometric features of the music audio track in view of the acoustic features, and determining a mood of the music audio track in view of the geometric features.

Abstract: A computing device identifies a first codeword in a first codebook to represent short-timescale information of frames in a time-based data item segmented at intervals and identifies a second codeword in a second codebook to represent long-timescale information of the frames. The computing device generates a third codebook based on the first codeword and the second codeword for the frames to add long-timescale information context to the short-timescale information of the frames.

Abstract: A computing system may process a plurality of audiovisual files to determine a mapping between audio characteristics and visual characteristics. The computing system may process an audio playlist to determine audio characteristics of the audio playlist. The computing system may determine, using the mapping, visual characteristics that are complementary to the audio characteristics of the audio playlist. The computing system may search a plurality of images to find one or more image(s) that have the determined visual characteristics. The computing system may link or associate the one or more image(s) that have the determined visual characteristics to the audio playlist such that the one or more images are displayed on a screen of the computing device during playback of the audio playlist.

Abstract: A system computes a vectorial representation for each of a set of initial patches in an image and compares the vectorial representation for each initial patch with vectorial representations of nearby patches. Each nearby patch is within a distance from an initial patch. The system applies an ordinal coding algorithm on the comparison results between the vectorial representations for the initial patches and vectorial representations of nearby patches to generate a two-dimensional representation of the image indicating a repeating pattern within the image.

Abstract: The disclosure includes a system and method for generating audio snippets from a subset of audio tracks. In some embodiments an audio snippet is an audio summary of a group or collection of songs.

Abstract: Methods and systems for generating playlists of media items with audio data are disclosed. Based on two received feature sets, media items corresponding to each feature set are identified. Transition characteristics are also received. Based on the identified media items and transition characteristics, a dynamic playlist is generated that transitions from media items having characteristics of the first feature set to media items having characteristics of the second feature set. Each time the playlist is generated, it may include a different set of media items.

Abstract: Generating a playlist may include designating a seed track in an audio library; identifying audio tracks in the audio library having constructs that are within a range of a corresponding construct of the seed track, where the constructs for the audio tracks are derived from frequency representations of the audio tracks, and the corresponding construct for the seed track is derived from a frequency representation of the seed track; and generating the playlist using at least some of the audio tracks that were identified.

Abstract: Methods and systems for generating playlists of media items with audio data are disclosed. Based on two received feature sets, media items corresponding to each feature set are identified. Transition characteristics are also received. Based on the identified media items and transition characteristics, a dynamic playlist is generated that transitions from media items having characteristics of the first feature set to media items having characteristics of the second feature set. Each time the playlist is generated, it may include a different set of media items.

Abstract: Methods and systems for generating playlists of media items with audio data are disclosed. Based on two received feature sets, media items corresponding to each feature set are identified. Transition characteristics are also received. Based on the identified media items and transition characteristics, a dynamic playlist is generated that transitions from media items having characteristics of the first feature set to media items having characteristics of the second feature set. Each time the playlist is generated, it may include a different set of media items.

Abstract: Meaningful words or phrases may be extracted from the information and used as tags. Weights may be determined for the tags, and tag clouds may be generated for the items. The tag clouds may be stored to a data store. Information specifying a tag cloud may be received. Recommended items for which the tag clouds most closely match the specified tag cloud may be identified. Standard vector space distance calculations, for example the cosine distance between the tag clouds, may be used to determine cloud similarity. The results may be filtered to optimize relevance, novelty and familiarity in accordance with preferences of the user. The recommended items may be displayed to a user interface. Users may interact with the user interface to steer the recommendations towards more relevant content.

Abstract: Method and apparatus for transparent, steerable recommendations. A steerable recommender uses tag clouds including descriptive tags and associated weights to generate recommendations. Users may dynamically interact with the recommender via a user interface to steer the recommendations. A tag cloud for an item is displayed, items for which associated tag clouds are most similar to the displayed tag cloud are identified, and the items are displayed as recommendations. The strength of similarity of the items to the displayed tag cloud may be displayed. The user may modify a tag cloud, for example by changing the weight of a tag or by adding or removing a tag, and the recommendations may be automatically updated to reflect the modification. A recommended item may be selected to display the tag cloud corresponding to the item. A user may select a user interface element to request information on why a particular item was recommended.