Abstract: The assistive hearing device implementations described herein assist hearing impaired users of the device by using automated speech transcription to generate text representing speech received in audio signals which can then be read in a synthesized voice tailored to overcome a user's hearing deficiencies. A speech recognition engine recognizes speech in received audio and converts the speech of the received audio to text. Once the speech is converted to text, a text-to-speech engine can convert the text to synthesized speech that can be enhanced and output in a voice that compensates for the hearing loss profiles of a user of the assistive hearing device. By transcribing received speech into text the assistive hearing device implementations described herein eliminate background noise from the audio signal. By converting the transcribed text into a synthesized voice that is easier to understand to hearing impaired persons, their hearing deficiencies can be remedied.

Abstract: The personal translator implementations described herein provide a speech translation device that pairs with a computing device to translate in-person conversations. The speech translation device can be wearable. In one implementation the personal translator comprises a speech translation device with at least one microphone that captures input signals representing nearby speech of a first user/wearer of the device and at least one other nearby person in a conversation in two languages; a wireless communication unit that sends the captured input signals representing speech to a nearby computing device, and receives for each language in the conversation, language translations from the computing device; and at least one loudspeaker that outputs the language translations to the first user/wearer and at least one other nearby person. The language translations in text form can be displayed on a display at the same time the language translations are output to the loudspeaker(s).

Abstract: The present invention may be used to analyze subject content, search and analyze reference content, compare the subject and reference content for similarity, and output comparison reports between the subject and reference content. The present invention may incorporate and utilize text from intrinsic and/or extrinsic subject documents. The analysis may employ a variety of metrics, including scores generated from a natural language processing system, scores based on classification similarity, scores based on proximity similarity, and in the case of analysis of patent documents, scores based on measurement of claims.

Abstract: The present invention may be used to analyze subject content, search and analyze reference content, compare the subject and reference content for similarity, and output comparison reports between the subject and reference content. The present invention may incorporate and utilize text from intrinsic and/or extrinsic subject documents. The analysis may employ a variety of metrics, including scores generated from a natural language processing system, scores based on classification similarity, scores based on proximity similarity, and in the case of analysis of patent documents, scores based on measurement of claims.

Abstract: A method of translation includes uploading a source text portion to a back end processor. The back end processor identifies a subset of translation knowledge associated with the source text portion. The back end processor downloads the subset to a front end processor. A translation engine runs on the front end processor. The translation engine generates a translation of the source text portion as a function of the subset.

Abstract: A machine translation system is trained to generate confidence scores indicative of a quality of a translation result. A source string is translated with a machine translator to generate a target string. Features indicative of translation operations performed are extracted from the machine translator. A trusted entity-assigned translation score is obtained and is indicative of a trusted entity-assigned translation quality of the translated string. A relationship between a subset of the extracted features and the trusted entity-assigned translation score is identified.

Abstract: In one embodiment of the present invention, a decoder receives a dependency tree as a source language input and accesses a set of statistical models that produce outputs combined in a log linear framework. The decoder also accesses a table of treelet translation pairs and returns a target dependency tree based on the source dependency tree, based on access to the table of treelet translation pairs, and based on the application of the statistical models.

Abstract: In one embodiment of the present invention, a decoder receives a dependency tree as a source language input and accesses a set of statistical models that produce outputs combined in a log linear framework. The decoder also accesses a table of treelet translation pairs and returns a target dependency tree based on the source dependency tree, based on access to the table of treelet translation pairs, and based on the application of the statistical models.

Abstract: In one embodiment of the present invention, a decoder receives a dependency tree as a source language input and accesses a set of statistical models that produce outputs combined in a log linear framework. The decoder also accesses a table of treelet translation pairs and returns a target dependency tree based on the source dependency tree, based on access to the table of treelet translation pairs, and based on the application of the statistical models.

Abstract: In one embodiment of the present invention, a decoder receives a dependency tree as a source language input and accesses a set of statistical models that produce outputs combined in a log linear framework. The decoder also accesses a table of treelet translation pairs and returns a target dependency tree based on the source dependency tree, based on access to the table of treelet translation pairs, and based on the application of the statistical models.

Abstract: A method translates a textual input in a first language to a textual output in a second language. An input logical form is generated based on the textual input. When a plurality of transfer mappings in a transfer mapping database match the input logical form (or at least a portion thereof) one or more of those plurality of matching transfer mappings is selected based on a predetermined metric. Textual output is generated based on the selected transfer logical form.

Abstract: A method of training a natural language processing unit applies a candidate learning set to at least one component of the natural language unit. The natural language unit is then used to generate a meaning set from a first corpus. A second meaning set is generated from a second corpus using a second natural language unit and the two meaning sets are compared to each other to form a score for the candidate learning set. This score is used to determine whether to modify the natural language unit based on the candidate learning set.

Abstract: A method of decoding an input semantic structure to generate an output semantic structure. A set of transfer mappings are provided. A score is calculated for at least one transfer mapping in the set of transfer mappings using a statistical model. At least one transfer mapping is selected based on the score and used to construct the output semantic structure.

Abstract: A machine translation system is trained to generate confidence scores indicative of a quality of a translation result. A source string is translated with a machine translator to generate a target string. Features indicative of translation operations performed are extracted from the machine translator. A trusted entity-assigned translation score is obtained and is indicative of a trusted entity-assigned translation quality of the translated string. A relationship between a subset of the extracted features and the trusted entity-assigned translation score is identified.

Abstract: The present invention can be used in a natural language processing system to determine a relationship (such as similarity in meaning) between two textual segments. The relationship can be identified or determined based on logical graphs generated from the textual segments. A relationship between first and second logical graphs is determined. This is accomplished regardless of whether there is an exact match between the first and second logical graphs. In one embodiment, the first graph represents an input textual discourse unit. The second graph, in one embodiment, represents information in a lexical knowledge base (LKB). The input graph can be matched against the second graph, if they have similar meaning, even if the two differ lexically or structurally.

Abstract: A method and system for processing messages is provided. In a preferred embodiment of the present invention, a message scheduler, a job process, and a format resolution module are used. The message scheduler identifies when a new message is to be processed, schedules the new message for processing, invokes the format resolution module to determine a method of converting data in the message to an appropriate format for a destination device or file, and invokes a job process. The format resolution module determines an appropriate method for converting data in the message from a format acceptable to the source devices or files to a format acceptable to the destination devices or files and creates a target message containing a reference to a destination device or file. The job process sends the data between the source devices or files to a destination device or file and performs the appropriate conversion.

Abstract: A multitasking, graphical windowing operating system for an office machine supporting real time processing, including a method for supporting real time processing in the operating system. The operating system includes a kernel having a non-preemptive scheduler for scheduling windowing applications and a preemptive scheduler for scheduling real time applications. The kernel includes a messaging subsystem for communication among process in the system including both the real time and windowing applications, and further includes an event semaphore maintained by the kernel to manage scheduling. The method includes grouping windowing applications together for scheduling purposes and scheduling windowing applications non-preemptively. The method further includes determining priority of real time applications and scheduling real time applications preemptively with the windowing applications based on priority.

Abstract: A system and method for exchanging data processing capabilities between computers. The computers exchange capabilities so that data transfer between the computers may be made in the most efficient data format possible for the two computers. A first computer, which will receive a data file, sends a list of data processing capabilities to a second computer, which will transmit the data file to the first computer. The transmitting computer examines the capabilities list of the receiving computer as well as its own capabilities list and determines the most efficient data format for the transfer. The transmitting computer may process the data file into an intermediate format for efficient data transfer so that the receiving computer will process the intermediate data file into the desired data format. The capabilities list can be cached for future communication between the computers. The system can update the capabilities list and inform other computers whether their cached capabilities list is current.

Abstract: An method and system for increasing the compatibility of a fax machine enables one to make a fax machine compatible with at least one other fax machine feature set. The invention includes selecting a compatibility module to handle a fax transmission based on a frame of information provided by another fax machine. The compatibility module interprets this information and maps it to a capabilities object. A messaging protocol module reads this capabilities object to determine the available capabilities.

Abstract: A method and system for processing messages is provided. In a preferred embodiment of the present invention, a message scheduler, a job process, and a format resolution module are used. The message scheduler identifies when a new message is to be processed, schedules the new message for processing, invokes the format resolution module to determine a method of converting data in the message to an appropriate format for a destination device or file, and invokes a job process. The format resolution module determines an appropriate method for converting data in the message from a format acceptable to the source devices or files to a format acceptable to the destination devices or files and creates a target message containing a reference to a destination device or file. The job process sends the data between the source devices or files to a destination device or file and performs the appropriate conversion.