Abstract: Systems and methods for generating authentic digital memorabilia are described. A signor may be provided a digital photograph. The signor's signature, written message, or voice message may be received. Biometric authentication or verification may be performed on the signor's handwriting or voice sample through comparison with stored samples. If the verification signifies a high likelihood signor's handwriting or voice sample is authentic, creation of digital memorabilia is performed by embedding signor's signature or written message in a digital photograph and linking the signor's voice message with the photograph. The digital memorabilia is accompanied by a certificate of authenticity and distributed to a customer or displayed on a website.

Abstract: A real time medical communication system for sending Notifications of medical Alerts includes a data translation layer for receiving real time medical data from one or more sources via a network and an Alerts engine. The Alerts engine may include a message processing module including an entity extraction module configured to extract entities from the real time medical data; and a fragment generation module configured to define fragments comprising events of interest for defining one or more medical Alerts. The Alerts engine may further include an Alert generation module that may include fragment query and evaluation modules for analyzing received real time medical data for defined fragments and generating one or more medical Alerts therefrom. A Notification module may also be provided for sending Notifications of Alerts to users.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a sequence generation neural network. One of the methods includes obtaining a batch of training examples; for each of the training examples: processing the training network input in the training example using the neural network to generate an output sequence; for each particular output position in the output sequence: identifying a prefix that includes the system outputs at positions before the particular output position in the output sequence, for each possible system output in the vocabulary, determining a highest quality score that can be assigned to any candidate output sequence that includes the prefix followed by the possible system output, and determining an update to the current values of the network parameters that increases a likelihood that the neural network generates a system output at the position that has a high quality score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for speech recognition. One method includes obtaining an input acoustic sequence, the input acoustic sequence representing an utterance, and the input acoustic sequence comprising a respective acoustic feature representation at each of a first number of time steps, processing the input acoustic sequence using a first neural network to convert the input acoustic sequence into an alternative representation for the input acoustic sequence, processing the alternative representation for the input acoustic sequence using an attention-based Recurrent Neural Network (RNN) to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings; and generating a sequence of substrings that represent a transcription of the utterance.

Abstract: A speech recognition neural network system includes an encoder neural network and a decoder neural network. The encoder neural network generates an encoded sequence from an input acoustic sequence that represents an utterance. The input acoustic sequence includes a respective acoustic feature representation at each of a plurality of input time steps, the encoded sequence includes a respective encoded representation at each of a plurality of time reduced time steps, and the number of time reduced time steps is less than the number of input time steps. The encoder neural network includes a time reduction subnetwork, a convolutional LSTM subnetwork, and a network in network subnetwork. The decoder neural network receives the encoded sequence and processes the encoded sequence to generate, for each position in an output sequence order, a set of sub string scores that includes a respective sub string score for each substring in a set of substrings.

Abstract: A computer-implemented method for training a neural network that is configured to generate a score distribution over a set of multiple output positions. The neural network is configured to process a network input to generate a respective score distribution for each of a plurality of output positions including a respective score for each token in a predetermined set of tokens that includes n-grams of multiple different sizes. Example methods described herein provide trained neural networks which produce results with improved accuracy compared to the state of the art, e.g. translations that are more accurate compared to the state of the art, or more accurate speech recognition compared to the state of the art.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a sequence generation neural network. One of the methods includes obtaining a batch of training examples; for each of the training examples: processing the training network input in the training example using the neural network to generate an output sequence; for each particular output position in the output sequence: identifying a prefix that includes the system outputs at positions before the particular output position in the output sequence, for each possible system output in the vocabulary, determining a highest quality score that can be assigned to any candidate output sequence that includes the prefix followed by the possible system output, and determining an update to the current values of the network parameters that increases a likelihood that the neural network generates a system output at the position that has a high quality score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for speech recognition. One method includes obtaining an input acoustic sequence, the input acoustic sequence representing an utterance, and the input acoustic sequence comprising a respective acoustic feature representation at each of a first number of time steps; processing the input acoustic sequence using a first neural network to convert the input acoustic sequence into an alternative representation for the input acoustic sequence; processing the alternative representation for the input acoustic sequence using an attention-based Recurrent Neural Network (RNN) to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings; and generating a sequence of substrings that represent a transcription of the utterance.

Abstract: A speech recognition neural network system includes an encoder neural network and a decoder neural network. The encoder neural network generates an encoded sequence from an input acoustic sequence that represents an utterance. The input acoustic sequence includes a respective acoustic feature representation at each of a plurality of input time steps, the encoded sequence includes a respective encoded representation at each of a plurality of time reduced time steps, and the number of time reduced time steps is less than the number of input time steps. The encoder neural network includes a time reduction subnetwork, a convolutional LSTM subnetwork, and a network in network subnetwork. The decoder neural network receives the encoded sequence and processes the encoded sequence to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings.

Abstract: Systems and methods for generating authentic digital memorabilia are described. A signor may be provided a digital photograph. The signor's signature, written message, or voice message may be received. Biometric authentication or verification may be performed on the signor's handwriting or voice sample through comparison with stored samples. If the verification signifies a high likelihood signor's handwriting or voice sample is authentic, creation of digital memorabilia is performed by embedding signor's signature or written message in a digital photograph and linking the signor's voice message with the photograph. The digital memorabilia is accompanied by a certificate of authenticity and distributed to a customer or displayed on a website.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a sequence generation neural network. One of the methods includes obtaining a batch of training examples; for each of the training examples: processing the training network input in the training example using the neural network to generate an output sequence; for each particular output position in the output sequence: identifying a prefix that includes the system outputs at positions before the particular output position in the output sequence, for each possible system output in the vocabulary, determining a highest quality score that can be assigned to any candidate output sequence that includes the prefix followed by the possible system output, and determining an update to the current values of the network parameters that increases a likelihood that the neural network generates a system output at the position that has a high quality score.

Abstract: Generally, the present disclosure is directed to systems and methods that generate augmented training data for machine-learned models via application of one or more augmentation techniques to audiographic images that visually represent audio signals. In particular, the present disclosure provides a number of novel augmentation operations which can be performed directly upon the audiographic image (e.g., as opposed to the raw audio data) to generate augmented training data that results in improved model performance. As an example, the audiographic images can be or include one or more spectrograms or filter bank sequences.

Abstract: A real time medical communication system for sending Notifications of medical Alerts includes a data translation layer for receiving real time medical data from one or more sources via a network and an Alerts engine. The Alerts engine may include a message processing module including an entity extraction module configured to extract entities from the real time medical data; and a fragment generation module configured to define fragments comprising events of interest for defining one or more medical Alerts. The Alerts engine may further include an Alert generation module that may include fragment query and evaluation modules for analyzing received real time medical data for defined fragments and generating one or more medical Alerts therefrom. A Notification module may also be provided for sending Notifications of Alerts to users.

Abstract: A real time medical communication system for sending Notifications of medical Alerts includes a data translation layer for receiving real time medical data from one or more sources via a network and an Alerts engine. The Alerts engine may include a message processing module including an entity extraction module configured to extract entities from the real time medical data; and a fragment generation module configured to define fragments comprising events of interest for defining one or more medical Alerts. The Alerts engine may further include an Alert generation module that may include fragment query and evaluation modules for analyzing received real time medical data for defined fragments and generating one or more medical Alerts therefrom. A Notification module may also be provided for sending Notifications of Alerts to users.

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for generating a data set that associates each text segment in a vocabulary of text segments with a respective numeric embedding. In one aspect, a method includes providing, to an image search engine, a search query that includes the text segment; obtaining image search results that have been classified as being responsive to the search query by the image search engine, wherein each image search result identifies a respective image; for each image search result, processing the image identified by the image search result using a convolutional neural network, wherein the convolutional neural network has been trained to process the image to generate an image numeric embedding for the image; and generating a numeric embedding for the text segment from the image numeric embeddings for the images identified by the image search results.

Abstract: A speech recognition neural network system includes an encoder neural network and a decoder neural network. The encoder neural network generates an encoded sequence from an input acoustic sequence that represents an utterance. The input acoustic sequence includes a respective acoustic feature representation at each of a plurality of input time steps, the encoded sequence includes a respective encoded representation at each of a plurality of time reduced time steps, and the number of time reduced time steps is less than the number of input time steps. The encoder neural network includes a time reduction subnetwork, a convolutional LSTM subnetwork, and a network in network subnetwork. The decoder neural network receives the encoded sequence and processes the encoded sequence to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings.

Abstract: A cloud system may create and support multiple network offerings for virtual machines in a cloud zone. Physical networks comprising sets of network elements, such as routers, gateways, firewalls, load balancers, and other network hardware, may be created and updated within a zone. Network offerings may be defined and associated, using tags or other techniques, with virtual machine networks, physical networks and/or network elements. Cloud end users may request specific network offerings when creating virtual machines, or may request to move existing virtual machines from one network offering to another. The cloud system may use the requested network offering to identify the virtual machine network, physical network, and/or network elements corresponding to the requested network offering. The cloud system may allocate a new virtual machine network and configure the network elements within the associated physical network to provide network services to the virtual machine.

Abstract: A cloud system may create and support multiple network offerings for virtual machines in a cloud zone. Physical networks comprising sets of network elements, such as routers, gateways, firewalls, load balancers, and other network hardware, may be created and updated within a zone. Network offerings may be defined and associated, using tags or other techniques, with virtual machine networks, physical networks and/or network elements. Cloud end users may request specific network offerings when creating virtual machines, or may request to move existing virtual machines from one network offering to another. The cloud system may use the requested network offering to identify the virtual machine network, physical network, and/or network elements corresponding to the requested network offering. The cloud system may allocate a new virtual machine network and configure the network elements within the associated physical network to provide network services to the virtual machine.

Abstract: The present invention relates to novel series of amine-containing flavonoids and compositions containing the compounds, as well as the synthesis and the use of the same. The invention also relates to methods of treatment and prevention of diseases, in particular, parasitic infections including Leishmaniasis, comprising administration of the compounds.

Abstract: Systems and methods for generating authentic digital memorabilia are described. A signor may be provided a digital photograph. The signor's signature, written message, or voice message may be received. Biometric authentication or verification may be performed on the signor's handwriting or voice sample through comparison with stored samples. If the verification signifies a high likelihood signor's handwriting or voice sample is authentic, creation of digital memorabilia is performed by embedding signor's signature or written message in a digital photograph and linking the signor's voice message with the photograph. The digital memorabilia is accompanied by a certificate of authenticity and distributed to a customer or displayed on a website.