Abstract: A “media stream customizer” customizes buffered media streams by inserting one or more media objects into the stream to maintain an approximate buffer level. Specifically, when media objects such as songs, jingles, advertisements, etc., are deleted from the buffered stream (based on some user specified preferences), the buffer level will decrease. Therefore, over time, as more objects are deleted, the amount of the media stream being buffered continues to decrease, thereby limiting the ability to perform additional deletions from the stream. To address this limitation, the media stream customizer automatically chooses one or more media objects to insert back into the stream, and ensures that the inserted objects are consistent with any surrounding content of the media stream, thereby maintaining an approximate buffer level. In addition, the buffered content can also be stretched using pitch preserving audio stretching techniques to further compensate for deletions from the buffered stream.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: An information dissemination system provides users information related to topics extracted from event classes. Event classes can generally be thought of as scripts that specify topics and actions for obtaining information related to the topics. The event classes are executed to obtain information related to the particular event class. The information dissemination system identifies a user event that is of interest to a user. The information dissemination system then identifies an event class that corresponds to the user event. The information dissemination system then performs the actions specified for the event class, obtains the action results, and renders the action results to the user.

Abstract: A technique for generating high-resolution bitmaps from low-resolution bitmaps. A low-resolution bitmap is magnified to form a magnified image. Edge detection is performed on the magnified image to find high contrast edges. A plurality of image patches of the magnified image are generated. These images patches are analyzed by performing connected components analysis on each of them using the high contrast edges to produce a plurality of foreground and background decisions determining whether a portion of an image patch is a background or a foreground region. Then the contrast of one or more pixels in each of the plurality of image patches is enhanced based on the foreground and background decisions. Finally, the system and method of the invention combines the luminance of the enhanced output pixels with the color values generated by the magnification algorithm. This produces a high-resolution bitmap from the contrast-enhanced pixels.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: An information dissemination system provides users information related to topics extracted from event classes. Event classes can generally be thought of as scripts that specify topics and actions for obtaining information related to the topics. The event classes are executed to obtain information related to the particular event class. The information dissemination system identifies a user event that is of interest to a user. The information dissemination system then identifies an event class that corresponds to the user event. The information dissemination system then performs the actions specified for the event class, obtains the action results, and renders the action results to the user.

Abstract: A system and method facilitating compression of bi-level images with explicit representation of ink clusters is provided. The present invention includes a cluster shape estimator that analyzes connected component information, extracts clusters and stores the cluster in a global dictionary, a page dictionary or a store of unclustered shapes. A bitmap estimation from clusters component determines dictionary positions for clusters stored in the global dictionary which are then encoded. A cluster position estimator determines page positions of clusters of the global dictionary and/or the page dictionary that are then encoded. Further, the global dictionary, the page dictionary and the store of unclustered shapes are also encoded.

Abstract: A system that facilitates organization of emails comprises a clustering component that clusters a plurality of emails and creates topics for emails by assigning key phrases extracted from emails within one or more clusters. An organization component then utilizes the key phrases to organize documents. Furthermore, the organization component can comprise a probability component that determines a probability that a document belongs to a certain topic.

Abstract: Systems and methods for encoding and decoding document images are disclosed. Document images are segmented into multiple layers according to a mask. The multiple layers are non-binary. The respective layers can then be processed and compressed separately in order to achieve better compression of the document image overall. A mask is generated from a document image. The mask is generated so as to reduce an estimate of compression for the combined size of the mask and multiple layers of the document image. The mask is then employed to segment the document image into the multiple layers. The mask determines or allocates pixels of the document image into respective layers. The mask and the multiple layers are processed and encoded separately so as to improve compression of the document image overall and to improve the speed of so doing. The multiple layers are non-binary images and can, for example, comprise a foreground image and a background image.

Abstract: A technique for generating high-resolution bitmaps from low-resolution bitmaps. A low-resolution bitmap is magnified to form a magnified image. Edge detection is performed on the magnified image to find high contrast edges. A plurality of image patches of the magnified image are generated. These images patches are analyzed by performing connected components analysis on each of them using the high contrast edges to produce a plurality of foreground and background decisions determining whether a portion of an image patch is a background or a foreground region. Then the contrast of one or more pixels in each of the plurality of image patches is enhanced based on the foreground and background decisions. Finally, the system and method of the invention combines the luminance of the enhanced output pixels with the color values generated by the magnification algorithm. This produces a high-resolution bitmap from the contrast-enhanced pixels.

Abstract: A system and method facilitating document image compression utilizing a mask separating a foreground of a document image from a background is provided. The invention includes a pixel energy analyzer adapted to partition regions into a foreground and background. The invention further provides for a merge region component adapted to attempt to merge regions if the merged region would not exceed a threshold energy. Merged regions are partitioned into a new foreground and new background. Thereafter, a mask storage component stores the partitioning information in a binary mask.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.

Abstract: A “media stream customizer” customizes buffered media streams by inserting one or more media objects into the stream to maintain an approximate buffer level. Specifically, when media objects such as songs, jingles, advertisements, etc., are deleted from the buffered stream (based on some user specified preferences), the buffer level will decrease. Therefore, over time, as more objects are deleted, the amount of the media stream being buffered continues to decrease, thereby limiting the ability to perform additional deletions from the stream. To address this limitation, the media stream customizer automatically chooses one or more media objects to insert back into the stream, and ensures that the inserted objects are consistent with any surrounding content of the media stream, thereby maintaining an approximate buffer level. In addition, the buffered content can also be stretched using pitch preserving audio stretching techniques to further compensate for deletions from the buffered stream.

Abstract: Systems and methods for performing clustering of a document image are disclosed. A property of an extracted mark from a document is compared to the properties of the existing clusters. If the property of the mark fails to match any of the properties of the existing clusters, the mark is added as a new cluster to the existing cluster. One property that can be utilized is x size and y size, which is the width and height, of the existing clusters. Another property that can be employed is ink size, which refers to the ratio of black pixels to total pixels in a cluster. Yet another property that can be utilized is a reduced mark or image, which is a pixel size reduced version the bitmap of the mark and/or cluster. The above properties can be employed to identify mismatches and reduce the number of bit by bit comparisons performed.

Abstract: The invention facilitates adaptive compression of multi-level images, such as captured digital images of a whiteboard, etc., encoding a bitstream comprising a color image component and a black-and-white image component. Either or both of a color and a black-and-white image can be output to a user based on user desires, receiving device capabilities, etc.

Abstract: The present invention relates to a system and methodology to facilitate automatic generation of mnemonic audio portions or segments referred to as audio thumbnails. A system is provided for summarizing audio information. The system includes an analysis component to determine common features in an audio file and a mnemonic detector to extract fingerprint portions of the audio file based in part on the common features in order to generate a thumbnail of the audio file. The generated thumbnails can then be employed to facilitate browsing or searching audio files in order to mitigate listening to longer portions or segments of such files.

Abstract: The present invention relates to a system and methodology to facilitate automatic management and pruning of audio files residing in a database. Audio fingerprinting is a powerful tool for identifying streaming or file-based audio, using a database of fingerprints. Duplicate detection identifies duplicate audio clips in a set, even if the clips differ in compression quality or duration. The present invention can be provided as a self-contained application that it does not require an external database of fingerprints. Also, a user interface provides various options for managing and pruning the audio files.