Abstract: A computer program product, for automatically editing a medical record transcription, resides on a computer-readable medium and includes computer-readable instructions for causing a computer to obtain a first medical transcription of a dictation, the dictation being from medical personnel and concerning a patient, analyze the first medical transcription for presence of a first trigger phrase associated with a first standard text block, determine that the first trigger phrase is present in the first medical transcription if an actual phrase in the first medical transcription corresponds with the first trigger phrase, and insert the first standard text block into the first medical transcription.

Abstract: Techniques for use in medical coding include applying a natural language understanding engine to a free-form text documenting at least one clinical patient encounter to generate a set of one or more medical billing codes for the patient encounter. A user interface may be provided, configured to allow one or more human users to review and correct the generated set of medical billing codes. Within the user interface, in response to user selection of a first medical billing code of the generated set of medical billing codes, at least a portion of a government-authorized codebook for the first medical billing code may be displayed, and a position of the first medical billing code may be indicated in the displayed portion of the codebook.

Abstract: Presenting natural-language-understanding (NLU) results can include redundancies and awkward sentence structures. In an embodiment of the present invention, a method includes, responsive to receiving a result to a NLU query, loading a matching template of a plurality of templates stored in a memory. Each template has mask fields associated with at least one property. The method compares the properties of the mask fields of each of the templates to properties of the query and properties of the result, and selects the matching template. The method further completes the matching template by inserting fields of the result into corresponding mask fields of the matching template. The method may further suppress certain mask fields of the matching template to increase brevity and improve the naturalness of the response when appropriate based on the results of the NLU query. The method further presents the completed matching template to a user via a display.

Abstract: Aspects of the disclosure provide systems and methods for facilitating dictation. Speech input may be provided to an audio input device of a computing device. A speech recognition engine at the computing device may obtain text corresponding to the speech input. The computing device may transmit the text to a remotely-located storage device. A login webpage that includes a session identifier may be accessed from a target computing device also located remotely relative to the storage device. The session identifier may be transmitted to the storage device and, in response, a text display webpage may be received at the target computing device. The text display webpage may include the speech-derived text and may be configured to automatically copy the text to a copy buffer of the target computing device. The speech-derived text may also be provided to native applications at target computing devices or NLU engines for natural language processing.

Abstract: A method and a system for generating, with the assistance of a computer system (12), a medical report (18) suitable for automatic billing, where an electronic template (39) suited for a specific patient's condition is selected out of a plurality of given electronic templates stored in storage means (15); personal data of the specific patient's and previously stored in storage means (11) are automatically entered into the selected electronic template; and medical report text passages and instructions are entered into the selected template by dictating and using a speech recognition system (13); additionally, condition data are automatically entered on the basis of condition information as far as stored in storage means (7) into the selected template, and code data associated with these condition information are automatically embedded in the selected template; and when entering medical report text passages, at least one predetermined voice macro stored in the storage means (16) together with code data embedded

Abstract: A method, computer program product, and computing system for acoustic speech localization, comprising receiving, via a plurality of microphones, a plurality of audio signals. Modulation properties of the plurality of audio signals may be analyzed. Speech sounds may be localized from the plurality of audio signals based upon, at least in part, the modulation properties of the plurality of audio signals.

Abstract: Techniques for learning front-end speech recognition parameters as part of training a neural network classifier include obtaining an input speech signal, and applying front-end speech recognition parameters to extract features from the input speech signal. The extracted features may be fed through a neural network to obtain an output classification for the input speech signal, and an error measure may be computed for the output classification through comparison of the output classification with a known target classification. Back propagation may be applied to adjust one or more of the front-end parameters as one or more layers of the neural network, based on the error measure.

Abstract: The method comprises receive first audio comprising speech from a user of a computing device, detecting an end of speech in the first audio, generating an ASR result based, at least in part, on a portion of the first audio prior to the detected end of speech, determining whether a valid action can be performed by a speech-enabled application installed on the computing device using the ASR result, and processing second audio when it is determined that a valid action cannot be performed by the speech-enabled application using the ASR result.

Abstract: A method, computer program product, and computing system for tracking encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information obtained via one or more machine vision systems. The machine vision encounter information is processed to identify one or more humanoid shapes.

Abstract: A system and method for detecting multi-tone sirens despite environmental noises that may be present obtains a microphone input signal, applies, in real time, a time-frequency analysis to the microphone input signal to determine a time-frequency representation, provides at least one multi-tone model that has a plurality of tone duration patterns, performs multi-tone siren detection on the time-frequency representation, the detection based on the at least one multi-tone model and factoring of doppler shifts, and generates a detection result that can be used in systems for automated vehicles.

Abstract: Methods, systems, computer-readable media, and apparatuses for providing search disambiguation using contextual information and domain ontologies are presented. In some embodiments, a computing device may receive a natural language input from a user. The computing device may identify a plurality of hypotheses for the natural language input. The computing device may map the plurality of hypotheses to one or more concepts of a plurality of concepts of an ontology by annotating the one or more concepts. The ontology may include the plurality of concepts respectively connected by a plurality of relations. The computing device may determine that there is an imperfect match between the annotated one or more concepts and annotations of answers. In response, the computing device may disambiguate the annotated one or more concepts using the ontology. The computing device may present output to the user based on the disambiguation.

Abstract: Multiple natural language understanding (NLU) interpretation selection models may be generated. The NLU interpretation selection models may include a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type and one or more specialized NLU interpretation selection models, each of which may be specific to a particular set of NLU interpretations type. The specialized NLU interpretation selection model(s) may be utilized to process natural language input data comprising data corresponding to their respective sets of NLU interpretations type(s). The generic NLU interpretation selection model may be utilized to process natural language input data comprising data that does not correspond to the sets of NLU interpretations type(s) associated with the specialized NLU interpretation selection model(s).

Abstract: A method, performed by at least one computer, the method comprising using the at least one computer to perform acts of accessing information specifying at least one user-specified condition specified by a user and at least one corresponding user-specified action, the user-specified action to be performed when the user-specified condition is met; determining whether the at least one user-specified condition is met; and when it is determined that the at least one user-specified condition is met, causing a virtual assistant executing on a mobile device different from the at least one computer to perform the at least one user-specified action.

Abstract: The present disclosure is directed towards a method for scheduling data packets in a multi-channel packet processing environment. The method may include receiving one or more data packets associated with an incoming signal and inserting the one or more data packets into a queue. The method may further include monitoring a time delay associated with each of the one or more data packets, wherein the time delay indicates a difference between packet arrival and packet departure times. The method may also include sorting the time delay results based upon an increasing order of time delay and determining a total number of data packets associated with each of a plurality of channels. The method may also include scheduling a data packet for processing based upon, at least in part, at least one of the sorted time delay results and the total number of data packets associated with each channel.

Abstract: Embodiments of the present invention perform speaker identification and verification by first prompting a user to speak a phrase that includes a common phrase component and a personal identifier. Then, the embodiments decompose the spoken phrase to locate the personal identifier. Finally, the embodiments identify and verify the user based on the results of the decomposing.

Abstract: Techniques for error correction using a history list comprising at least one misrecognition and correction information associated with each of the at least one misrecognitions indicating how a user corrected the associated misrecognition. The techniques include converting data input from a user to generate a text segment, determining whether at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, if the at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, obtaining the correction information associated with the at least one misrecognition, and correcting the at least a portion of the text segment based, at least in part, on the correction information.

Abstract: A method for prompting user input for a multimodal interface including the steps of providing a multimodal interface to a user, where the interface includes a visual interface having a plurality of input regions, each having at least one input field; selecting an input region and processing a multi-token speech input provided by the user, where the processed speech input includes at least one value for at least one input field of the selected input region; and storing at least one value in at least one input field.

Abstract: Disclosed methods and systems are directed to concept identification and capture. The methods and systems may include receiving, by a device, a first natural language input comprising one or more terms, and analyzing the first natural language input via a natural language processing engine to identify one or more named entities associated with the one or more terms, wherein each of the one or more named entities is associated with at least one category of a plurality of categories. The methods and systems may also include detecting a text field configured to receive text, the text field being associated with one of the plurality of categories, and inputting into the text field one of the one or more identified named entities based on the text field being associated with a same category as the one of the one or more named entities.

Abstract: An assignment device (1) assigns word class information (WKI) to one or more words of text information (ETI). Based on word-class sequence information (WK-AI) formed from this assigned word class information (WKI), actions (A) are executed in order to notify the user of conflicts or to provide the user with background information (HI) relating to words in the text information (TT).

Abstract: Techniques for medical coding include applying a natural language understanding (NLU) engine to a free-form text documenting a clinical patient encounter, to derive a first set of one or more medical billing codes for the clinical patient encounter and a link between each code in the first set and a corresponding portion of the free-form text. The first set of codes may be compared to a second set of one or more medical billing codes approved by one or more human users for the patient encounter, to identify at least one code in the first set that overlaps with at least one code in the second set. The code in the second set approved by the one or more human users may be retained instead of the overlapping code in the first set derived by the NLU engine.