Abstract: Methods, systems and computer programs for automatic, highly accurate machine comprehension of a plurality of segments of free form unstructured text in a natural language. The system answers a plurality of complex, free-form questions asked in a natural language, based on the totality of input text. The system further uses a multi-dimensional data model to measure the total effects of actions/verbs acting on various unique nouns present in the input text. The system may convert the questions into another multi-dimensional data model and may then compare the two data models in program memory to derive the answers to the posed questions. The system may then automatically detect unknown words and optionally look them up in digital information sources, such as online dictionaries and encyclopedias, to fill in the gaps in knowledge to answer the questions with expert-like reliability.

Abstract: A system and method of verifying the identity of an authorized user in an authorized user group for enabling secure access to one or more services via a device includes receiving first voice information from a speaker through the device, calculating a confidence score based on a comparison of the first voice information with a stored voice model associated with the authorized user and specific to the authorized user, interpreting the first voice information as a specific service request, identifying a minimum confidence score for initiating the specific service request, determining whether or not the confidence score exceeds the minimum confidence score, and initiating the specific service request if the confidence score exceeds the minimum confidence score.

Abstract: A voice signal processor detects background noise sections to reflect characteristics of the background noise on the Wiener filter coefficient to be used for suppressing noise components of input voice signals. In the voice signal processor, directivity signal generators form directivity signals having a directivity pattern. The directivity signals are used by a coherence calculator to obtain coherence, which is in turn used by a targeted voice section detector to detect a targeted voice section. A background noise section detector detects background noise sections containing no voice signal. When a background noise section is detected, a WF adapter uses characteristics of background noise in the detected temporal section to calculate a new WF coefficient.

Abstract: An apparatus is provided with a device storing machine readable code and a processor executing the machine readable code. The machine readable code includes sound setting code and audio processing code. The sound setting code detects use of a microphone and sets sound characteristics that are suitable for conversation in response to detecting the use of the microphone. The audio processing code processes sound on the basis of the sound characteristics set by the sound setting code.

Abstract: An encoding method executed by a computer, the method includes converting by the computer information about a transient included in a low-frequency component of an audio signal into information about a transient included in a high-frequency component of the audio signal, detecting, by the computer the transient of the high-frequency component of the audio signal based on the high-frequency component of the audio signal and on the information about the transient of the high-frequency component obtained by the converting; and encoding, by the computer the high-frequency component of the audio signal based on the transient detected by the detecting.

Abstract: A computer-implemented method identifies textual statement relationships. Textual statement pairs including a first and second textual statement are identified, and parsed word group pairs are extracted from first and second textual statements. The parsed word groups are compared, and a parsed word score for each statement pair is calculated. Word vectors for the first and second textual statements are created and compared. A word vector score is calculated based on the comparison of the word vectors for the first and second textual statements. A match score is determined for the textual statement pair, with the match score being representative of at least one of the parsed word score and the word vector score.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for assigning saliency weights to words of an ASR model. The saliency values assigned to words within an ASR model are based on human perception judgments of previous transcripts. These saliency values are applied as weights to modify an ASR model such that the results of the weighted ASR model in converting a spoken document to a transcript provide a more accurate and useful transcription to the user.

Abstract: A semiconductor integrated circuit device for voice recognition includes: a signal processing unit which generates a feature pattern representing a state of distribution of frequency components of an input voice signal; a voice recognition database storage unit which stores a voice recognition database including a standard pattern representing a state of distribution of frequency components of plural phonemes; a conversion list storage unit which stores a conversion list including plural words or sentences to be conversion candidates; a standard pattern extraction unit which extracts a standard pattern corresponding to character data representing the first syllable of each word or sentence included in the conversion list, from the voice recognition database; and a matching detection unit which compares the feature pattern generated from the first syllable of the voice signal with the extracted standard pattern and thus detects the matching of the syllable.

Abstract: A speech intelligibility enhancement (SIE) system and method is described that improves the intelligibility of a speech signal to be played back by an audio device when the audio device is located in an environment with loud acoustic background noise. In an embodiment, the audio device comprises a near-end telephony terminal and the speech signal comprises a speech signal received over a communication network from a far-end telephony terminal for playback at the near-end telephony terminal.

Abstract: Methods and systems for receiving applications are described. A device, such as a wearable computing device, may receive an input, which may be verbal, motion, or text, for example. The device may parse the input to recognize any keywords and may further identify applications associated with the recognized keywords. The device may determine a priority list for the identified applications based at least in part on a relevance associated with the recognized keywords. In addition, the device may provide for display the priority list of the applications. The device may receive a request to access an application from the plurality of applications, and in response to the request to access the application, install the application. The device may further execute the installed application to perform a function based at least in part on the verbal input, which may be executed without additional input after installation.

Abstract: The present invention provides a method for identifying a turn, such as a sentence or phrase, for addition to a platform dialog comprising a plurality of turns. Lexical features of each of a set of candidate turns relative to one or more turns in the platform dialog are determined. Semantic features associated with each candidate turn and associated with the platform dialog are determined to identify one or more topics associated with each candidate turn and with the platform dialog. Lexical features of each candidate turn are compared to lexical features of the platform dialog and semantic features associated with each candidate turn are compared to semantic features of the platform dialog to rank the candidate turns based on similarity of lexical features and semantic features of each candidate turn to lexical features and semantic features of the platform dialog.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: Methods, systems, and apparatus, for pattern recognition. One aspect includes a pattern recognizing engine that includes multiple pattern recognizer processors that form a hierarchy of pattern recognizer processors. The pattern recognizer processors include a child pattern recognizer processor at a lower level in the hierarch and a parent pattern recognizer processor at a higher level of the hierarchy, where the child pattern recognizer processor is configured to provide a first complex recognition output signal to a pattern recognizer processor at a higher level than the child pattern recognizer processor, and the parent pattern recognizer processor is configured to receive as an input a second complex recognition output signal from a pattern recognizer processor at a lower level than the parent pattern recognizer processor.

Abstract: In one embodiment, collecting a plurality of words from texts submitted by one or more users; for each of a plurality of communication categories, determining a usage frequency of each of one or more of the words within the communication category based on the texts; and constructing one or more customized dictionaries that each comprise a different blending of selected words.

Abstract: In one embodiment, constructing one or more customized dictionaries for a particular user, each of the customized dictionaries comprising a different blending of one or more frequently used words collected from texts submitted by one or more users; and in response to the user inputting text to an electronic device, selecting one of the customized dictionaries and utilizing it to aid the particular user in inputting text.

Abstract: Provided are a coding device, a communication processing device, and a coding method, whereby processing operation load (computational load) is significantly reduced for a configuration which computes either frame energy or sub-frame energy of an input signal, using auto-correlation operations, without causing a decline in the precision of either the frame energy or the sub-frame energy. In a coding device (101), a sub-frame energy computation unit (201) computes the sub-frame energy by substituting the sum of input signal auto-correlation operations in a first range with the sum of auto-correlation operations in a second range which differs at least partially from the first range.

Abstract: In an automatic speech recognition (ASR) processing system, ASR processing may be configured to process speech based on multiple channels of audio received from a beamformer. The ASR processing system may include a microphone array and the beamformer to output multiple channels of audio such that each channel isolates audio in a particular direction. The multichannel audio signals may include spoken utterances/speech from one or more speakers as well as undesired audio, such as noise from a household appliance. The ASR device may simultaneously perform speech recognition on the multi-channel audio to provide more accurate speech recognition results.

Abstract: A mobile wireless communications device may include a housing and a wireless transceiver carried by the housing. The mobile wireless communications device may also include audio transducer carried by the housing, and a controller cooperating with the wireless transceiver to perform at least one wireless communications function. The controller may also cooperate with the at least one audio transducer to convert speech input through the audio transducer to converted text, determine a proposed modification for the converted text, and output from the audio output transducer the proposed modification for the converted text.

Abstract: A system, method, and computer program are provided for identifying message content to send to users based on the users' language characteristics. Language characteristics are extracted from user-generated content and language characteristic scores are assigned to each user. The users are clustered into groups using the language characteristic scores. The system sends test messages with different message content to at least a subset of each group's users and the response rates are measured. For each group, a message content to which the group is most responsive is identified and is associated with the group. Language characteristics from a new user's user-generated content are extracted and language characteristic scores are assigned to the new user. The group to which the new user belongs is identified using the new user's language characteristic scores. A message is sent to the new user with the message content previously associated with the identified group.

Abstract: According to one embodiment, approximate named-entity extraction from a dictionary that includes entries is provided, where each of the entries includes one or more words. Words are read from the entries of the dictionary, and network resources are searched to determine a frequency of occurrence of the words on the network resources. In view of the frequency of occurrence of the words located on the network resources, domain relevancy of the words in the entries of the dictionary is determined. A domain repository is created using top-ranked words as determined by the domain relevancy of the words. In view of the domain repository, signatures for both the entries of the dictionary and strings of an input document are computed. The strings of the input document are filtered by comparing the signatures of the strings against the signatures of the entries to identify approximate-match entity names.