Abstract: Apparatuses, systems, and techniques to enhance video are disclosed. In at least one embodiment, one or more neural networks are used to create, from a first video, a second video having one or more additional video frames.

Abstract: Disclosed are apparatuses, systems, and techniques that may use machine learning for implementing generative text-to-speech models. The techniques include identifying a mapping of speech characteristics (SC) on a target distribution of a latent variable using a non-linear transformation for at least a subset of the SC. Parameters of the non-linear transformation are determined using a neural network that approximates a statistics of the SC with a statistics predicted for the SC based on the identified mapping and the target distribution of the latent variable.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Systems and methods for isothermal amplification of nucleic acids in a ratiometric manner are disclosed. Methods of isothermal amplification of nucleic acids are convenient for areas that lack reliable electricity and/or funding for precision lab equipment. However, these methods typically result in non-ratiometric amplification of target sequences, thus preventing quantitative analysis or application of the results, such as for diagnostic testing. Systems and methods herein provide a method of isothermal amplification that ratiometrically amplifies target sequences, thus expanding the reach of diagnostics into remote and/or economically disadvantaged areas.

Abstract: Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

Abstract: Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images using one or more pixel weights determined based, at least in part, on one or more sub-pixel offset values.

Abstract: Apparatuses, systems, and techniques to enhance video. In at least one embodiment, one or more neural networks are used to create, from a first video, a second video having a higher frame rate, higher resolution, or reduced number of missing or corrupt video frames.

Abstract: Apparatuses, systems, and techniques to enhance video are disclosed. In at least one embodiment, one or more neural networks are used to create, from a first video, a second video having one or more additional video frames.

Abstract: A neural network architecture is disclosed for performing image in-painting using partial convolution operations. The neural network processes an image and a corresponding mask that identifies holes in the image utilizing partial convolution operations, where the mask is used by the partial convolution operation to zero out coefficients of the convolution kernel corresponding to invalid pixel data for the holes. The mask is updated after each partial convolution operation is performed in an encoder section of the neural network. In one embodiment, the neural network is implemented using an encoder-decoder framework with skip links to forward representations of the features at different sections of the encoder to corresponding sections of the decoder.

Abstract: A neural network architecture is disclosed for performing video frame prediction using a sequence of video frames and corresponding pairwise optical flows. The neural network processes the sequence of video frames and optical flows utilizing three-dimensional convolution operations, where time (or multiple video frames in the sequence of video frames) provides the third dimension in addition to the two-dimensional pixel space of the video frames. The neural network generates a set of parameters used to predict a next video frame in the sequence of video frames by sampling a previous video frame utilizing spatially-displaced convolution operations. In one embodiment, the set of parameters includes a displacement vector and at least one convolution kernel per pixel. Generating a pixel value in the next video frame includes applying the convolution kernel to a corresponding patch of pixels in the previous video frame based on the displacement vector.

Abstract: An article handling device is provided. In one embodiment, a system for article handling is provided. The system has first and second article handling devices that each have one or more gripping assemblies arranged around their periphery. The gripping assemblies are selectably movable between an open position and a closed position based on the relative position of the first and second article handling devices.

Abstract: A system and method for managed device data collection includes a data collector controller for control of monitoring activity of networked multifunction peripherals. A user interface includes a display rendering a plurality of processor rendered interactive user configuration screens. Displayed configuration screens solicit and receive corresponding user input. The configuring screens facilitate setting device user interaction including setting a network address, network connectivity testing, modification of device certificates, changing network settings, and a testing discovery, registration or data transfer mechanism for multifunction peripheral device data collection. A data storage stores user selection data received via rendered configuration screens and the processor outputs stored user selection data as configuration data for data collection from the multifunction peripherals.

Abstract: A system and method for managed device data collection includes a data collector controller for control of monitoring activity of networked multifunction peripherals. A user interface includes a display rendering a plurality of processor rendered interactive user configuration screens. Displayed configuration screens solicit and receive corresponding user input. The configuring screens facilitate setting device user interaction including setting a network address, network connectivity testing, modification of device certificates, changing network settings, and a testing discovery, registration or data transfer mechanism for multifunction peripheral device data collection. A data storage stores user selection data received via rendered configuration screens and the processor outputs stored user selection data as configuration data for data collection from the multifunction peripherals.

Abstract: An article handling device is provided. In one embodiment, a system for article handling is provided. The system has first and second article handling devices that each have one or more gripping assemblies arranged around their periphery. The gripping assemblies are selectably movable between an open position and a closed position based on the relative position of the first and second article handling devices.

Abstract: Products (e.g., books) often include a significant amount of informative textual information that can be used in identifying the item. An input query image is a photo (e.g., a picture taken using a mobile phone) of a product. The photo is taken from an arbitrary angle and orientation, and includes an arbitrary background (e.g., a background with significant clutter). From the query image, the identification server retrieves the corresponding clean catalog image from a database. For example, the database may be a product database having a name of the product, image of the product, price of the product, sales history for the product, or any suitable combination thereof. The retrieval is performed by both matching the image with the images in the database and matching text retrieved from the image with the text in the database.