Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.

This application relates to a speech recognition method and apparatus, and a computer-readable storage medium, and the method includes: obtaining a first loss function of a speech separation and enhancement model and a second loss function of a speech recognition model; performing back propagation based on the second loss function to train an intermediate model bridged between the speech separation and enhancement model and the speech recognition model, to obtain a representation model; fusing the first loss function and the second loss function, to obtain a target loss function; and jointly training the speech separation and enhancement model, the representation model, and the speech recognition model based on the target loss function, and ending the training when a preset convergence condition is met.

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

Alert directives and focused alert directives allow a user to provide feedback to a behavioral recognition system to always or never publish an alert for certain events. Such an approach bypasses the normal publication methods of the behavioral recognition system yet does not obstruct the system's learning procedures.

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

Techniques are disclosed for building a dictionary of words from combinations of symbols generated based on input data. A neuro-linguistic behavior recognition system includes a neuro-linguistic module that generates a linguistic model that describes data input from a source (e.g., video data, SCADA data, etc.). To generate words for the linguistic model, a lexical analyzer component in the neuro-linguistic module receives a stream of symbols, each symbol generated based on an ordered stream of normalized vectors generated from input data. The lexical analyzer component determines words from combinations of the symbols based on a hierarchical learning model having one or more levels. Each level indicates a length of the words to be identified at that level. Statistics are evaluated for the words identified at each level. The lexical analyzer component identifies one or more of the words having statistical significance.

Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.

A method for performing an iteration of an output of a trained GAN may be provided. The method comprises receiving an object as input for the GAN, determining a set of features of the input by the generator adversarial network, generating, by the GAN, at least one modification to one feature of the set of features of the object, generating as output of the GAN the received object as a basis, and the generated modification building a modified object, capturing a feedback signal, and receiving the feedback signal as input by the GAN in a feedback loop for a next iteration. Moreover, the method comprises repeating the determination of a set of features, the generation of at least one modification, the generation of the output and the caption of the feedback signal in the next iteration, wherein as object the modified object is used as the object.

Techniques are disclosed for normalizing and publishing alerts using a behavioral recognition-based video surveillance system configured with an alert normalization module. Certain embodiments allow a user of the behavioral recognition system to provide the normalization module with a set of relative weights for alert types and a maximum publication value. Using these values, the normalization module evaluates an alert and determines whether its rareness value exceed a threshold. Upon determining that the alert exceeds the threshold, the module normalizes and publishes the alert.