Abstract: Disclosed herein are system, method, and computer program product embodiments for machine learning systems to process interactive communications between at least two participants. Speech and text, within the interactive communications, are analyzed using machine learning classifiers to extract prosodic, semantic and key phrase cues located within the interactive communications to identify changes to emotion, sentiments and key phrases. A summary of the interactive communications between a first participant and a second participant is generated at least, in-part, based on the extracted prosodic, semantic and key phrase cues and the summary is highlighted based on any of the changes to emotion, the sentiments or the key phrases.

Abstract: Disclosed herein are system, method, and computer program product embodiments for machine learning systems to process interactive communications between at least two participants. Speech and text, within the interactive communications, are analyzed using machine learning classifiers to extract prosodic, semantic and key phrase cues located within the interactive communications to identify changes to emotion, sentiments and key phrases. A summary of the interactive communications between a first participant and a second participant is generated at least, in-part, based on the extracted prosodic, semantic and key phrase cues and the summary is highlighted based on any of the changes to emotion, the sentiments or the key phrases.

Abstract: Disclosed herein are system, method, and computer program product embodiments for machine learning systems to process interactive communications between at least two participants. Speech and text, within the interactive communications, are analyzed using machine learning classifiers to extract prosodic, semantic and key phrase cues located within the interactive communications to identify changes to emotion, sentiments and key phrases. A summary of the interactive communications between a first participant and a second participant is generated at least, in-part, based on the extracted prosodic, semantic and key phrase cues and the summary is highlighted based on any of the changes to emotion, the sentiments or the key phrases.

Abstract: Computer program products include program code readable/executable by one or more processors, and configured to cause the processor(s) to: receive an image of a part or all of a document selected from a group consisting of: a gift card, an invoice, a bill, a receipt, a sales order, an insurance claim, a medical insurance document, and a benefits document; perform optical character recognition (OCR) on the image; extract at least a partial address of a sender of the document; compare the at least partial address of the sender to a plurality of addresses in a first database; and identify one or more of: textual information specific to the sender; and data formatting specific to the sender. The code configured to cause the processor to receive the image, perform the OCR, extract and compare the (at least partial) address, and identify sender-specific information is preferably a processor of a mobile device.

Abstract: In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner, or multifunction peripheral. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.

Abstract: In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner, or multifunction peripheral. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.

Abstract: Computer program products include program code readable/executable by one or more processors, and configured to cause the processor(s) to: receive an image of a part or all of a document selected from a group consisting of: a gift card, an invoice, a bill, a receipt, a sales order, an insurance claim, a medical insurance document, and a benefits document; perform optical character recognition (OCR) on the image; extract at least a partial address of a sender of the document; compare the at least partial address of the sender to a plurality of addresses in a first database; and identify one or more of: textual information specific to the sender; and data formatting specific to the sender. The code configured to cause the processor to receive the image, perform the OCR, extract and compare the (at least partial) address, and identify sender-specific information is preferably a processor of a mobile device.

Abstract: In one embodiment, a method includes receiving an image of a document; performing optical character recognition (OCR) on the image; extracting an address of a sender of the document from the image based on the OCR; comparing the extracted address with content in a first database; identifying complementary textual information in a second database based on the address; and at least one of: extracting additional content from the image of the document; correcting one or more OCR errors in the document using the complementary textual information, and normalizing data from the document prior to determining a validity of the document using at least one of the complementary textual information and predefined business rules. At least one of the aforementioned operations is performed using a processor of a mobile device. Exemplary systems and computer program products are also disclosed.

Abstract: In one embodiment, a method includes receiving an image of a document; performing optical character recognition (OCR) on the image; extracting an address of a sender of the document from the image based on the OCR; comparing the extracted address with content in a first database; identifying complementary textual information in a second database based on the address; and at least one of: extracting additional content from the image of the document; correcting one or more OCR errors in the document using the complementary textual information, and normalizing data from the document prior to determining a validity of the document using at least one of the complementary textual information and predefined business rules. At least one of the aforementioned operations is performed using a processor of a mobile device. Exemplary systems and computer program products are also disclosed.