Abstract: A system and method are presented for adaptive skill level assignments of agents in contact center environments. A client and a service collaborate to automatically determine the effectiveness of an agent handling an interaction that has been routed using skills-based routing. Evaluation operations may be performed including emotion detection, transcription of audio to text, keyword analysis, and sentiment analysis. The results of the evaluation are aggregated with other information such as the interaction's duration, agent skills and agent skill levels, and call requirement skills and skill levels, to update the agent's profile which is then used for subsequent routing operations.

Abstract: A computing device, method, and a non-transitory computer readable medium for articulation training for hearing impaired persons is disclosed. The computing device comprises a database including stored mel-frequency cepstral representations of audio recordings associated with text and/or images related to the audio recordings, a microphone configured to receive audible inputs and a display. The computing device is operatively connected to the database, the microphone and the display. The computing device includes circuitry and program instructions stored therein which when executed by one or more processors, cause the system to receive an audible input from the microphone, convert the audible input to a mel-frequency cepstral representation, search the database for a match of the mel-frequency cepstral representation to a stored mel-frequency cepstral representation and display the text and/or images related to the stored mel-frequency cepstral representation when the match is found.

Abstract: A method comprises inputting an audio signal into a machine learning circuit to compress the audio signal into a sequence of actuator signals. The machine learning circuit being trained by: receiving a training set of acoustic signals and pre-processing the training set of acoustic signals into pre-processed audio data. The pre-processed audio data including at least a spectrogram. The training further includes training the machine learning circuit using the pre-processed audio data. The neural network has a cost function based on a reconstruction error and a plurality of constraints. The machine learning circuit generates a sequence of haptic cues corresponding to the audio input. The sequence of haptic cues is transmitted to a plurality of cutaneous actuators to generate a sequence of haptic outputs.

Abstract: A system configured to process an incoming spoken utterance and to coordinate among multiple speechlet components to execute an action of the utterance, where a trained model considers user history and preference information to select the primary speechlet to execute the action as well as any intermediate speechlets that may be provide input data to the speechlet that will ultimately perform the action. The trained model may also consider current dialog information, feedback data, or other data when determining how to process a dialog.

Abstract: A system for improving dysarthria speech intelligibility and method thereof, are provided. In the system, user only needs to provides a set of paired corpus including a reference corpus and a patient corpus, and a speech disordering module can automatically generate a new corpus completely synchronous with the reference corpus, and the new corpus can be used as a training corpus for training a dysarthria voice conversion model. The present invention does not need to use a conventional corpus alignment technology or a manual manner to perform pre-processing on the training corpus, so that manpower cost and time cost can be reduced, and synchronization of the training corpus can be ensured, thereby improving both training and conversion qualities of the voice conversion model.

Abstract: Processing data for speech recognition by generating hypotheses from input data, assigning each hypothesis, a score according to a confidence level value and hypothesis ranking, executing a pass/fail grammar test against each hypothesis, generating replacement hypotheses according to grammar test failures, assigning each replacement hypothesis a score according to a number of hypothesis changes, and providing a set of hypotheses, wherein the set comprises at least one replacement hypotheses.

Abstract: A method of speaker authentication comprises: receiving a speech signal; dividing the speech signal into segments; and, following each segment, obtaining an authentication score based on said segment and previously received segments, wherein the authentication score represents a probability that the speech signal comes from a specific registered speaker. In response to an authentication request, an authentication result is output based on the authentication score.

Abstract: This disclosure describes systems and techniques receiving a request for information from a user and, in response, outputting the requested information along with unsolicited, interesting content that is related to, yet nonresponsive to, the requested information. In some instances, if the requested information is unknown, the techniques may output an indication that the information is unknown, followed by the additional, unsolicited, interesting content.

Abstract: An artificial intelligence apparatus for recognizing speech of a user includes a microphone, and a processor configured to receive, via the microphone, a sound signal corresponding to the speech of the user, acquire personalize identification information corresponding to the speech, recognize the speech from the sound signal using a global language model, calculate a reliability for the recognition, and if the calculated reliability exceeds a predetermined first reference value, update a personalized language model corresponding to the personalize identification information using the recognition result.

Abstract: A new model is introduced into a particular domain that receives a routing of a dialog from a speech processing component. A method associated with the model includes running a set of test utterances through the speech processing component that enables a spoken language dialog with a user to establish a base line score associated with processing for the set of test utterances. The speech processing component determines an intent of the user and routes the spoken language dialog to a network-based domain based on the intent. The method includes establishing an automatic test run of the set of test utterances to obtain a current score and, when a threshold associated with a difference between the current score and the base line score is breached, switching, at the network-based domain, from the false accept detection model to a second model.

Abstract: A method is described that includes processing text and speech from an input utterance using local overrides of default dictionary pronunciations. Applying this method, a word-level grammar used to process the tokens specifies at least one local word phonetic variant that applies within a specific production rule and, within a local context of the specific production rule, the local word phonetic variant overrides one or more default dictionary phonetic versions of the word. This method can be applied to parsing utterances where the pronunciation of some words depends on their syntactic or semantic context.

Abstract: Spoken language understanding techniques include training a dynamic neural network mask relative to a static neural network using only post-deployment training data such that the mask zeroes out some of the weights of the static neural network and allows some other weights to pass through and applying a dynamic neural network corresponding to the masked static neural network to input queries to identify outputs for the queries.

Abstract: This application relates generally to modifying visual data based on audio commands and more specifically, to performing complex operations that modify visual data based on one or more audio commands. In some embodiments, a computer system may receive an audio input and identify an audio command based on the audio input. The audio command may be mapped to one or more operations capable of being performed by a multimedia editing application. The computer system may perform the one or more operations to edit to received multimedia data.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a style feed including a plurality of original works by an author. An author-style model for the author is built based on the style feed by use of a selected neural network, and a publication is generated in the style of the author based on the author-style model.

Abstract: A computer-implemented method may include obtaining, by processor, a first message composed in a first language and obtaining, by the processor, a translated first message. The translated first message may include a translation of the first message from the first language to a second language. The method may further include determining, by the processor, that the translated first message includes a translation-generated additional meaning, and notifying, by the processor, the first user of the determination.

Abstract: The gain of an amplifier in a receiver operating in a cellular communication system is controlled by determining one or more gain variability metrics, which are then used to produce first and second threshold values. A frequency difference between a current carrier frequency and a target carrier frequency is ascertained and then compared to the threshold values. Target gain setting production is based on comparison results: If the frequency difference is larger than the first threshold, a first automatic gain control algorithm is performed; if the frequency difference is smaller than the first threshold and larger than the second threshold, a second automatic gain control algorithm is performed, wherein the second automatic gain control algorithm uses a current gain setting as a starting point; and if the frequency difference is smaller than both the first and second thresholds, the current gain setting is used as the target gain setting.

Abstract: A computer-implement voice command authentication method is provided. The method includes obtaining a sound signal stream; calculating a Signal-to-Noise Ratio (SNR) value of the sound signal stream; converting the sound signal stream into a Mel-Frequency Cepstral Coefficients (MFCC) stream; calculating a Dynamic Time Warping (DTW) distance corresponding to the MFCC stream according to the MFCC stream and one of a plurality of sample streams generated by the Gaussian Mixture Model with Universal Background Model (GMM-UBM); calculating, according to the MFCC stream and the sample streams, a Log-likelihood ratio value corresponding to the MFCC stream as a GMM-UBM score; determining whether the sound signal stream passes a voice command authentication according to the GMM-UBM score, the DTW distance and the SNR value; in response to determining that the sound signal stream passes the voice command authentication, determining that the sound signal stream is a voice stream spoken from a legal user.

Abstract: A method includes receiving a voice input at an electronic device. An ambiguity of the voice input is determined. The ambiguity is resolved based on contextual data. The contextual data includes at least one of: an image, a non-voice input comprising a gesture, a pointer of a pointing device, a touch, or a combination thereof.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for controlling a page. A specific embodiment of the method comprises: receiving voice information from a terminal and element information of at least one element in a displayed page; performing voice recognition on the voice information to acquire a voice recognition result, in response to determining the voice information being used for controlling the displayed page; matching the voice recognition result with the element content information of the at least one element; and generating page control information in response to determining successfully matching the voice recognition result with the element content information of the at least one element, and sending the page control information to the terminal to allow the terminal to control the displayed page based on the page control information.

Abstract: Voice control in a multi-talker and multimedia environment is disclosed. In one aspect, there is provided a method comprising: receiving a microphone signal for each zone in a plurality of zones of an acoustic environment; generating a processed microphone signal for each zone in the plurality of zones of the acoustic environment, the generating including removing echo caused by audio transducers in the acoustic environment from each of the microphone signals, and removing interference from each of the microphone signals; and performing speech recognition on the processed microphone signals.