Abstract: Structured hierarchies for communicating contextual information relating to a VoIP conversation are provided. The structured hierarchies are utilized for efficient communications of various amounts and types of contextual information over a VoIP conversation channel. Information identifying at least one structured hierarchy, which will be used to carry the contextual information, is transmitted during establishment of a conversation between two VoIP enhanced devices and prior to the exchange of contextual information. The structural hierarchy is selected from a set of predefined and declared structured hierarchies. Subsequently transmitted contextual information exchanged between two VoIP enhanced devices is represented in accordance with the identified structural hierarchy. Additionally, the structural hierarchies can be extensible by the addition of more definitions to the current structural hierarchies.

Abstract: A data sequence may be encoded in a plurality of layers of multiple description coding. The layers of multiple description coding may include a first and a second layer of multiple description coding. The first layer of multiple description coding may include an initial part of a data sequence as well as forward error correction code for the initial part. The second layer of multiple description coding may include a next part of the data sequence as well as forward error correction code for the next part. A first set of data sequence breakpoints may be determined for the first layer of multiple description coding. A second set of data sequence breakpoints may be determined for the second layer. The data sequence may be encoded in the plurality of layers of multiple description coding as a function of the first and second sets of data sequence breakpoints.

Abstract: Generally described, multimode authentication over a VoIP communication channel is provided. A calling client and a called client may be authenticated for a communication channel establishment. When a calling client requests a call connection with a called client, the calling client is authenticated for the communication channel, based on exchanged contextual information between the calling client and the called client. Likewise, the called client is authenticated for the communication channel by the calling client. Upon authentication, a communication channel is established, over which the calling client and the called client are allowed to exchange more contextual and voice/multimedia information. During a conversation, when a secured service is desired by any of the clients, a series of authentication processes can be performed to grant access to the secured service over the communication channel without loss of the communication channel connection.

Abstract: A data sequence may be encoded in a plurality of layers of multiple description coding. The layers of multiple description coding may include a first and a second layer of multiple description coding. The first layer of multiple description coding may include an initial part of a data sequence as well as forward error correction code for the initial part. The second layer of multiple description coding may include a next part of the data sequence as well as forward error correction code for the next part. A first set of data sequence breakpoints may be determined for the first layer of multiple description coding. A second set of data sequence breakpoints may be determined for the second layer. The data sequence may be encoded in the plurality of layers of multiple description coding as a function of the first and second sets of data sequence breakpoints.

Abstract: A method for operating a machine to perform unsupervised training of a set of character templates uses as the source of training samples an image source of character images, called glyphs, that need not be manually or automatically segmented or isolated prior to training. A recognition operation performed on the image source of character images produces a labeled glyph position data structure that includes, for each glyph in the image source, a glyph image position in the image source associating an estimated image location of the glyph in the image source with a character label paired with the glyph image position that indicates the character in the character set being trained. The labeled glyph position data and the image source are then used to determine sample image regions in the image source; each sample image region is large enough to contain at least a single glyph but need not be restricted in size to only contain a single glyph.

Abstract: A method for producing, or training, a set of character templates uses as the source of training samples an image source of character images, called glyphs, that are not previously segmented or isolated for training. Also used is a labeled glyph position data structure that includes, for each glyph in the image source, a glyph image position in the image source associating an image location of the glyph with a character label paired with the glyph image position that indicates the character in the character set being trained. The labeled glyph position data is used to identify a collection of glyph sample image regions in the image source for each character in the character set; each glyph sample image region is large enough to contain a glyph and typically contains adjacent glyphs for other characters.

Abstract: A technique for automatically training a set of character templates using unsegmented training samples uses as input a two-dimensional (2D) image of characters, called glyphs, as the source of training samples, a transcription associated with the 2D image as a source of labels for the glyph samples, and an explicit, formal 2D image source model that models as a grammar the structural and functional features of a set of 2D images that may be used as the source of training data. The input transcription may be a literal transcription associated with the 2D input image, or it may be nonliteral, for example containing logical structure tags for document formatting, such as found in markup languages. The technique uses spatial positioning information about the 2D image modeled by the 2D image source model and uses labels in the transcription to determine labeled glyph positions in the 2D image that identify locations of glyph samples.

Abstract: A method for establishing a relationship between a text image and a transcription associated with the text image uses conventional image processing techniques to identify one or more geometric attributes, or image parameters, of each of a sequence of regions of the text image. The transcription labels in the transcription are analyzed to determine a comparable set of parameters in transcription label sequence. A matching operation then matches the respective parameters of the two sequences to identify image regions that match with transcription regions. The result is an output data structure that minimally identifies image locations of interest to a subsequent operation that processes the text image. The output data structure may also pair each of the image locations of interest to a transcription location, in effect producing a set of labeled image locations. In one embodiment, the sequence of locations of words and their observed lengths in the text image are determined.