Abstract: Provided are a display apparatus, a control method thereof, a server, and a control method thereof. The display apparatus includes: a processor which processes a signal; a display which displays an image based on the processed signal; a first command receiver which receives a voice command; a storage which stores a plurality of voice commands said by a user; a second command receiver which receives a user's manipulation command; and a controller which, upon receiving the voice command, displays a list of the stored plurality of voice commands, selects one of the plurality of voice commands of the list according to the received user's manipulation command and controls the processor to process based on the selected voice command.

Abstract: In an example, there is disclosed a method of providing voice-activated network control (VANC), including: receiving a voice input; converting the voice input to a computer-usable form; parsing the voice input into key tokens; building a network policy macro from the key tokens; and causing commands based on the network policy macro to be executed on a target device. There is also disclosed one or more apparatuses for performing the method, and one or more computer-readable mediums having stored thereon executable instructions for realizing the method on a device.

Abstract: A system for detecting an original language of a translated document retrieves the translated document, and identifies a language of the retrieved document. The system calculates a language model for the language of the retrieved document (LM(RD)). The system calculates a distinct vector as a difference between LM(RD) and a common language model for the language of the retrieved document (LMT(RD)). The system obtains pair vectors for language model pairs associated with the language of the retrieved document, and calculates a vector distance between the distinct vector and each pair vector (or between the (LM(RD)) and each pair vector). The system identifies a given pair vector within a threshold vector distance, and calculates the confidence score. The system then identifies the original language corresponding to the given pair vector as the original language of the retrieved document, and retrieves an original document in the original language of the retrieved document.

Abstract: A system and method for temporarily disabling keyword detection to avoid detection of machine-generated keywords. A local device may operate two keyword detectors. The first keyword detector operates on input audio data received by a microphone to capture keywords uttered by a user. In these instances, the keyword may be detected by the first detector and the audio data may be transmitted to a remote device for processing. The remote device may generate output audio data to be sent to the local device. The local device may process the output audio data to determine that it also includes the keyword. The device may then disable the first keyword detector while the output audio data is played back by an audio speaker of the local device. Thus the local device may avoid detection of a keyword originating from the output audio. The first keyword detector may be reactivated after a time interval during which the keyword might be detectable in the output audio.

Abstract: A natural language user interface for computer-aided design systems (CAD) comprises a natural language command module including a parser, language database and a CAD model analyzer, and a natural language server module including a second, increased capability parser, a second, preferably larger language database and a CAD context database. The CAD model analyzer analyzes and retrieves associated CAD model information related to a parsed voice command and the CAD context database provides specific CAD related contextual information to facilitate parsing and interpreting CAD specific commands. The natural language server program module may also include an artificial intelligence based query generator and communicate through a network or cloud with resource providers such as third-party market places or suppliers to generate queries for retrieval of third party supplied information necessary to respond to or execute CAD specific voice commands.

Abstract: Provided herein is an electronic device and method of voice recognition, the method including analyzing an audio signal of a first frame when the audio signal is input and extracting a first feature value; determining a similarity between the first feature value extracted from the audio signal of the first frame and a first feature value extracted from an audio signal of a previous frame; analyzing the audio signal of the first frame and extracting a second feature value when the similarity is below a predetermined threshold value; and comparing the extracted first feature value and the second feature value and at least one feature value corresponding to a pre-defined voice signal and determining whether or not the audio signal of the first frame is a voice signal, and thus the electronic device may detect only a voice section from the audio signal while improving the processing speed.

Abstract: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.

Abstract: Systems and processes for converting speech-to-text are provided. In one example process, speech input can be received. A sequence of states and arcs of a weighted finite state transducer (WFST) can be traversed. A negating finite state transducer (FST) can be traversed. A virtual FST can be composed using a neural network language model and based on the sequence of states and arcs of the WFST. The one or more virtual states of the virtual FST can be traversed to determine a probability of a candidate word given one or more history candidate words. Text corresponding to the speech input can be determined based on the probability of the candidate word given the one or more history candidate words. An output can be provided based on the text corresponding to the speech input.

Abstract: Disclosed are a display apparatus, a voice acquiring apparatus and a voice recognition method thereof, the display apparatus including: a display unit which displays an image; a communication unit which communicates with a plurality of external apparatuses; and a controller which includes a voice recognition engine to recognize a user's voice, receives a voice signal from a voice acquiring unit, and controls the communication unit to receive candidate instruction words from at least one of the plurality of external apparatuses to recognize the received voice signal.

Abstract: A method for speech processing includes determining an unvoicing parameter for a first frame of a speech signal and determining a smoothed unvoicing parameter for the first frame by weighting the unvoicing parameter of the first frame and a smoothed unvoicing parameter of a second frame. The unvoicing parameter reflects a speech characteristic of the first frame. The smoothed unvoicing parameter of the second frame is weighted less heavily when the smoothed unvoicing parameter of the second frame is greater than the unvoicing parameter of the first frame. The method further includes computing a difference, by a processor, between the unvoicing parameter of the first frame and the smoothed unvoicing parameter of the first frame, and determining a classification of the first frame according to the computed difference. The classification includes unvoiced speech or voiced speech. The first frame is processed in accordance with the classification of the first frame.

Abstract: Techniques for naming devices via voice commands are described herein. For instance, a user may issue a voice command to a voice-controlled device stating, “you are the kitchen device”. Thereafter, the device may respond to voice commands directed, by name, to this device. For instance, the user may issue a voice command requesting to “play music on my kitchen device”. Given that the user has configured the device to respond to this name, the device may respond to the command by outputting the requested music.

Abstract: A system and method are presented for predicting speech recognition performance using accuracy scores in speech recognition systems within the speech analytics field. A keyword set is selected. Figure of Merit (FOM) is computed for the keyword set. Relevant features that describe the word individually and in relation to other words in the language are computed. A mapping from these features to FOM is learned. This mapping can be generalized via a suitable machine learning algorithm and be used to predict FOM for a new keyword. In at least one embodiment, the predicted FOM may be used to adjust internals of speech recognition engine to achieve a consistent behavior for all inputs for various settings of confidence values.

Abstract: Text is received from a first client. The text is associated with an electronic communication tool for communication to a second client. Candidate answers are generated based on the text using a question answering system. The question answering system generates the candidate answers based on a plurality of data sources, including at least one personalized data source and at least one informational data source. At least one of the candidate answers is provided to the second client. Each of the candidate answers provided to the second client is selectable.

Abstract: Text is received from a first client. The text is associated with an electronic communication tool for communication to a second client. Candidate answers are generated based on the text using a question answering system. The question answering system generates the candidate answers based on a plurality of data sources, including at least one personalized data source and at least one informational data source. At least one of the candidate answers is provided to the second client. Each of the candidate answers provided to the second client is selectable.

Abstract: Mechanisms, in a natural language processing (NLP) system are provided. The NLP system receives performance data for a performance to be provided by a human performer. The performance data comprises an objective to be achieved by the performance. The NLP system monitors channels of communication to identify natural language statements exchanged over the channels directed to the performance while the performance is being presented. The NLP system extracts feedback information from the natural language statements and generates aggregate feedback information. The NLP system evaluates an alignment of the aggregate feedback information with the objective and outputs a guidance output based on results of the evaluation. The guidance output guides the performer to modify presentation of the performance to more likely achieve the at least one objective based on the aggregate feedback information.

Abstract: A method is presented for forming the excitation signal for a glottal pulse model based parametric speech synthesis system. In one embodiment, fundamental frequency values are used to form the excitation signal. The excitation is modeled using a voice source pulse selected from a database of a given speaker. The voice source signal is segmented into glottal segments, which are used in vector representation to identify the glottal pulse used for formation of the excitation signal. Use of a novel distance metric and preserving the original signals extracted from the speakers voice samples helps capture low frequency information of the excitation signal. In addition, segment edge artifacts are removed by applying a unique segment joining method to improve the quality of synthetic speech while creating a true representation of the voice quality of a speaker.

Abstract: Disclosed is a unified speech and audio coding (USAC) audio signal encoding/decoding apparatus and method for digital radio services. An audio signal encoding method may include receiving an audio signal, determining a coding method for the received audio signal, encoding the audio signal based on the determined coding method, and configuring, as an audio superframe of a fixed size, an audio stream generated as a result of encoding the audio signal, wherein the coding method may include a first coding method associated with extended high-efficiency advanced audio coding (xHE-AAC) and a second coding method associated with existing advanced audio coding (AAC).

Abstract: A keyword detector includes a processor configured to calculate a feature vector for each frame from a speech signal, input the feature vector for each frame to a DNN to calculate a first output probability for each triphone according to a sequence of phonemes contained in a predetermined keyword and a second output probability for each monophone, for each of at least one state of an HMM, calculate a first likelihood representing the probability that the predetermined keyword is uttered in the speech signal by applying the first output probability to the HMM, calculate a second likelihood for the most probable phoneme string in the speech signal by applying the second output probability to the HMM, and determine whether the keyword is to be detected on the basis of the first likelihood and the second likelihood.

Abstract: A dictation device includes: an audio input device configured to receive a voice utterance including a plurality of words; a video input device configured to receive video of lip motion during the voice utterance; a memory portion; a controller configured according to instructions in the memory portion to generate first data packets including an audio stream representative of the voice utterance and a video stream representative of the lip motion; and a transceiver for sending the first data packets to a server end device and receiving second data packets including combined dictation based upon the audio stream and the video stream from the server end device. In the combined dictation, first dictation generated based upon the audio stream has been corrected by second dictation generated based upon the video stream.

Abstract: A computer receives a query including a plain text word. The computer determines whether at least one performance optimization parameter is configured. The computer identifies syllables within the plain text word that have a high probability of spelling errors. The computer selects each character in the syllables identified. The computer identifies a group of characters from a confusion matrix that are commonly confused with the character selected. For each character selected, the computer generates a set of characters including characters from the confusion matrix. The computer determines probabilities of omitting the selected characters and associates tags with one or more sets of characters based on the determined probabilities. The computer generates a regular expression by concatenating the sets of characters. The computer searches for a spelling of the plain text word that omits at least one character in the regular expression that is associated with a tag.