Abstract: Techniques are disclosed to optimize feature selection in generating betas for a feature dictionary of a neuro-linguistic Cognitive AI System. A machine learning engine receives a sample vector of input data to be analyzed by the neuro-linguistic Cognitive AI System. The neuro-linguistic Cognitive AI System is configured to generate multiple betas for each of a plurality of sensors. The machine learning engine identifies a sensor specified in the sample vector and selects optimization parameters for generating betas based on the identified sensor.

Abstract: A method, decoder, and program code for controlling a concealment method for a lost audio frame is provided. A first audio frame and a second audio frame of the received audio signal are decoded to obtain modified discrete cosine transform (MDCT) coefficients. Values of a first spectral shape based upon the MDCT coefficients decoded from the first audio frame decoded and values of a second spectral shape based upon MDCT coefficients decoded from the second audio frame decoded are determined, the spectral shapes each comprising a number of sub-bands. The values of the spectral shapes and frame energies of the first audio frame and second audio frame are transformed into representations of FFT based spectral analyses. A transient condition is detected based on the representations of the FFTs. Responsive to detecting the transient condition, the concealment method is modified by selectively adjusting a spectrum magnitude of a substitution frame spectrum.

Abstract: Aspects include methods, systems, and computer-program products providing virtual assistant domain functionality. A natural language query including one or more words is received. A collection of natural language modules is accessed. The collection natural language modules are configured to process sets of natural language queries. A natural language module, from the collection of natural language modules, is identified to interpret the natural language query. An interpretation of the natural language query is computed using the identified natural language module. A response to the natural language query is returned using the computed interpretation.

Abstract: In exemplary embodiments of the present invention systems and methods are provided to implement and facilitate cross-fading, interstitials and other effects/processing of two or more media elements in a personalized media delivery service so that each client or user has a consistent high quality experience. The effects or crossfade processing can occur on the broadcast, publisher or server-side, but can still be personalized to a specific user, thus still allowing a personalized experience for each individual user, in a manner where the processing burden is minimized on the downstream side or client device. This approach enables a consistent user experience, independent of client device capabilities, both static and dynamic.

Abstract: A system for removing noise from an audio signal is described. For example, noise caused by content playing in the background during a voice command or phone call may be removed from the audio signal representing the voice command or phone call. By removing noise, the signal to noise ratio of the audio signal may be improved.

Abstract: An encoder operable to filter audio signals into a plurality of frequency band components, generate quantized digital components for each band, identify a potential for pre-echo events within the generated quantized digital components, generate an approximate signal by decoding the quantized digital components using inverse pulse code modulation, generate an error signal by comparing the approximate signal with the sampled audio signal, and process the error signal and quantized digital components. The encoder operable to process the error signal by processing delayed audio signals and Q band values, determining the potential for pre-echo events from the Q band values, and determining scale factors and MDCT block sizes for the potential for pre-echo events.

Abstract: A method includes, during a teleconference between a first audio input/output device and a second audio input/output device, receiving, at an analysis and response device, a signal indicating a spoken command, the spoken command associated with a command mode. The method further includes, in response to receiving the signal, generating, at the device, a reply message based on the spoken command, the reply message to be output to one or more devices selected based on the command mode. The one or more devices includes the first audio input/output device, the second audio input/output device, or a combination thereof.

Abstract: An improved concept for coding sample values of a spectral envelope is obtained by combining spectrotemporal prediction on the one hand and context-based entropy coding the residuals, on the other hand, while particularly determining the context for a current sample value dependent on a measure of a deviation between a pair of already coded/decoded sample values of the spectral envelope in a spectrotemporal neighborhood of the current sample value. The combination of the spectrotemporal prediction on the one hand and the context-based entropy coding of the prediction residuals with selecting the context depending on the deviation measure on the other hand harmonizes with the nature of spectral envelopes.

Abstract: An apparatus for encoding directional audio coding parameters including diffuseness parameters and direction parameters includes: a parameter calculator for calculating the diffuseness parameters with a first time or frequency resolution and for calculating the direction parameters with a second time or frequency resolution; and a quantizer and encoder processor for generating a quantized and encoded representation of the diffuseness parameters and the direction parameters.

Abstract: Techniques are described for providing information during a service session, using an intelligent agent. The intelligent agent executes as a process to monitor communications exchanged during a service session between an individual and a service representative (SR) within a service environment. The agent analyzes the communications to identify questions or other topics that are posed by the individual during the service session. The agent retrieves stored data related to such questions or other topics, and generates a message to address each question or other topic. The message is injected into the service session to be presented to the individual, to supplement the conversation that is taking place between the SR and the individual. In some implementations, the agent monitors the communications, generates the message, and/or injects the message into the service session at least partly autonomously of any explicit action taken by the SR.

Abstract: A method of leveraging a dialogue history of a conversational computing interface to execute an updated dialogue plan. The method comprises maintaining an annotated dialogue history of the conversational computing interface. The annotated dialogue history includes a plurality of traced steps defining a data-flow including input data used to execute a context-dependent operation and output data recorded from a previous execution of the context-dependent operation. The method further comprises recognizing an updated dialogue plan including a prefix of executable steps and an updated executable step following the prefix. The method further comprises automatically computer-recognizing that the prefix of executable steps of the updated dialogue plan matches a corresponding prefix of traced steps in the annotated dialogue history. The method further comprises re-using the data-flow from the prefix of traced steps in the annotated dialogue history to automatically determine input data of the updated executable step.

Abstract: A method comprises receiving a new data set; identifying at least one prior data set of a plurality of prior data sets that matches the new data set; generating a natural language data science problem statement for the new data set based on information associated with the at least prior one data set that matches the new data set; outputting the generated natural language data science problem statement for user verification; and in response to receiving user input verifying the natural language generated data science problem statement, generating one or more AutoAI configuration settings for the new data set based on one or more AutoAI configuration settings associated with the at least one prior data set that matches the new data set.

Abstract: A method for adapting hotword recognition includes receiving audio data characterizing a hotword event detected by a first stage hotword detector in streaming audio captured by a user device. The method also includes processing, using a second stage hotword detector, the audio data to determine whether a hotword is detected by the second stage hot word detector in a first segment of the audio data. When the hotword is not detected by the second stage hotword detector, the method includes, classifying the first segment of the audio data as containing a negative hotword that caused a false detection of the hotword event in the streaming audio by the first stage hotword detector. Based on the first segment of the audio data classified as containing the negative hotword, the method includes updating the first stage hotword detector to prevent triggering the hotword event in subsequent audio data that contains the negative hotword.

Abstract: An apparatus for generating a decoded two-channel signal, comprising: a parametric decoder for providing parametric data for a second set of second spectral portions and a two-channel identification identifying for a second spectral portion of the second set of second spectral portions either a first two-channel representation for the second spectral portion of the second set of second spectral portions or a second two-channel representation for the second spectral portion of the second set of second spectral portions, the second two-channel representation being different from the first two-channel representation; and a frequency regenerator for regenerating the second spectral portion of the second set of second spectral portions depending on a first spectral portion of a first set of first spectral portions, the parametric data for the second spectral portion of the second set of second spectral portions and the two-channel identification for the second spectral portion of the second set of second spectral

Abstract: Methods, systems and apparatuses for computer-generated visualization of speech are described herein. An example method of computer-generated visualization of speech including at least one segment includes: generating a graphical representation of an object corresponding to a segment of the speech; and displaying the graphical representation of the object on a screen of a computing device. Generating the graphical representation includes: representing a duration of the respective segment by a length of the object and representing intensity of the respective segment by a width of the object; and placing, in the graphical representation, a space between adjacent objects.

Abstract: Disclosed herein are new techniques carried out by a computing system for determining delays of various components of an audio system to allow for accurate correction of these delays, which may improve the audio quality of live performances for listeners who hear audio reproduced by loudspeakers at live performance venues. In one implementation the computing system, which may comprise a transmitter device and one or more receiver devices, may be configured to perform functions, including receiving a first audio signal, receiving, via an audio input interface of the receiver, a second audio signal, and determining, based on the first audio signal and the second audio signal, an audio delay that is associated with the second audio signal. The computing system may be configured to perform further functions, including based on a determined cross-correlation between a downsampled audio signal and a filtered second audio signal, determining the audio signal delay.

Abstract: A device to perform speech enhancement includes one or more processors configured to obtain input spectral data based on an input signal. The input signal represents sound that includes speech. The one or more processors are also configured to process, using a multi-encoder transformer, the input spectral data and context data to generate output spectral data that represents a speech enhanced version of the input signal.

Abstract: Controlling a concealment method for a lost audio frame associated with a received audio signal is provided. At least one bin vector of a spectral representation for at least one tone is obtained, wherein the at least one bin vector includes three consecutive bin values for the at least one tone. Whether each of the three consecutive bin values has a complex value or a real value is determined. Responsive to the determination, the three consecutive bin values are processed to estimate a frequency of the at least one tone based on whether each bin value has a complex value or a real value.

Abstract: Technologies are disclosed for improving the efficiency of real-time audio processing, and specifically for improving the efficiency of continuously modifying a real-time audio signal. Efficiency is improved by reducing memory bandwidth requirements and by reducing the amount of processing used to modify the real-time audio signal. In some configurations, memory bandwidth requirements are reduced by selectively transferring active samples in the frequency domain—e.g. avoiding the transfer samples with amplitudes of zero or near-zero. This has particular importance when the specialized hardware retrieves samples from main memory in real-time. In some configurations, the amount of processing needed to modify the audio signal is reduced by omitting operations that do not meaningfully affect the output audio signal. For example, a multiplication of samples may be avoided when at least one of the samples has an amplitude of zero or near-zero.

Abstract: Systems and methods are described for training an artificial intelligence model to infer a log sourcetype of a log. For example, logs may have different log sourcetypes, and logs having the same log sourcetypes may have different messagetypes. The artificial intelligence model may be a machine learning model, and can be trained using training data that includes logs with known log sourcetypes. Each log can be tokenized, filtered, converted into a vector, and applied to a machine learning model as an input to perform the training. The machine learning model may output an inferred log sourcetype, which can be compared with the known log sourcetype to update model parameters to improve the machine learning model accuracy. The trained machine learning model may be trained to infer a log sourcetype of a log regardless of the messagetype of the log.