Mitsubishi Electric Research Laboratories, Inc.

Unified Access Communications

Bret Harsham

John R Hershey

Jonathan Le Roux

Daniel Nikolaev Nikovski

Chiori Hori

Bhiksha Ramakrishnan

Takaaki Hori

Shinji Watanabe

Garrett Weinberg

Bent Schmidt-Nielsen

Anthony Vetro

Tim Marks

Alan Sullivan

Anoop Cherian

Dirk Brinkman

Siheng Chen

Alan W Esenther

Evandro Bacci Gouvêa

Lalit Jain

Yi Luan

Systems and methods for a computer system for detecting anomalies in incoming communication from a sender to a receiver. Accepting a relationship structure defining a trained association model between the sender and the receiver, and the incoming communication. Accessing neural networks trained to detect anomalies in the incoming communication and classify the anomalies by type, subject to correspondence between content of the incoming communication and the trained association model between the sender and the receiver. Compute an updated association model, based on sender and the receivers organizational indications using the content of the incoming communication. Execute the neural networks by submitting the incoming communication and the updated association model to produce a result of anomaly detection and anomaly classification type. Execute a single sequence of defensive actions to deliver the incoming communication to the receiver, when the single sequence of defensive actions is above a predetermined delivering threshold.

System and method for using human relationship structures for email classification

A navigation system for providing driving instructions to a driver of a vehicle traveling on a route is provided. The driving instructions are generated by executing a multimodal fusion method that comprises extracting features from sensor measurements, annotating the features with directions for the vehicle to follow the route with respect to objects sensed by the sensors, and encoding the annotated features with a multimodal attention neural network to produce encodings. The encodings are transformed into a common latent space, and the transformed encodings are fused using an attention mechanism producing an encoded representation of the scene. The method further comprises decoding the encoded representation with a sentence generation neural network to generate a driving instruction and submitting the driving instruction to an output device.

Method and system for scene-aware interaction

A method for performing multi-label classification includes extracting a feature vector from an input vector including input data by a feature extractor, determining, by a label predictor, a relevant vector including relevant labels having relevant scores based on the feature vector, updating a binary masking vector by masking pre-selected labels having been selected in previous label selections, applying the updated binary masking vector to the relevant vector such that the relevant label vector is updated to exclude the pre-selected labels from the relevant labels, and selecting a relevant label from the updated relevant label vector based on the relevant scores of the updated relevant label vector.

Method and system for multi-label classification

A spoken language understanding (SLU) system receives a sequence of words corresponding to one or more spoken utterances of a user, which is passed through a spoken language understanding module to produce a sequence of intentions. The sequence of words are passed through a first subnetwork of a multi-scale recurrent neural network (MSRNN), and the sequence of intentions are passed through a second subnetwork of the multi-scale recurrent neural network (MSRNN). Then, the outputs of the first subnetwork and the second subnetwork are combined to predict a goal of the user.

Method for using a multi-scale recurrent neural network with pretraining for spoken language understanding tasks

An information system includes a prediction engine for predicting an action based on a set of driving state parameters, and a driving history, and a simulation engine for generating a hypothetical scenario by simulating one or a combination of at least one driving state parameter and at least part of the driving history, such that the prediction engine predicts the action for the hypothetical scenario.

Actions prediction for hypothetical driving conditions

A method delivers information to satisfy current needs of a driver of a vehicle, by first acquiring data related to a current state of the vehicle. The current state and a predictive model are passed to a predictive procedure to determine choice probabilities for nodes in a choice tree (CT). Based on the choice probabilities, information related to the current needs to the driver are selected from a database storing commercial and non-commercial information. Then, the information is delivered to the driver, wherein the delivering is autonomous of the driver.

Method and system for autonomously delivering information to drivers

A method for recognizing speech including a sequence of words determines a shape of a gesture and a location of the gesture with respect to a display device showing a set of interpretations of the speech. The method determines a type of the word sequence constraint based on the shape of the gesture and determines a value of the word sequence constraint based on the location of the gesture. Next, the speech is recognized using the word sequence constraint.

Determining word sequence constraints for low cognitive speech recognition

A method adapts a user interface of a vehicle navigation system. Based on an input vector representing a current state related to the vehicle, probabilities of actions are predicted to achieve a next state using a predictive model representing previous states. Then, a subset of the actions with highest probabilities that minimize a complexity of interacting with the vehicle navigation system are displayed in the vehicle.

Method and system for dynamically adapting user interfaces in vehicle navigation systems to minimize interaction complexity

A system and a method recognize speech including a sequence of words. A set of interpretations of the speech is generated using an acoustic model and a language model, and, for each interpretation, a score representing correctness of an interpretation in representing the sequence of words is determined to produce a set of scores. Next, the set of scores is updated based on a consistency of each interpretation with a constraint determined in response to receiving a word sequence constraint.

System and method for recognizing speech

An information retrieval system stores and retrieves documents using particles and a particle-based language model. A set of particles for a collection of documents in a particular language is constructed from training documents such that a perplexity of the particle-based language model is substantially lower than the perplexity of a word-based language model constructed from the same training documents. The documents can then be converted to document particle graphs from which particle-based keys are extracted to form an index to the documents. Users can then retrieve relevant documents using queries also in the form of particle graphs.

Method for indexing for retrieving documents using particles

A computer implemented method facilitates a user interaction via a speech-based user interface. The method acquires spoken input from a user in a form of a phrase of one or more words. It further determines, using a plurality of different domains, whether the phrase is a query or a command. If the phrase is the query the method retrieves and presents relevant items from a plurality of databases. If the phrase is a command, the method performs an operation.

Method for interacting with users of speech recognition systems

A centralized computer network management system that simultaneously configures and monitors computers in a computer network. The computer network management system allows a network administrator to describe the computer network according to both its physical topology and logical groups of machines and users in the computer network. Each network device, computer, or groups of network devices and computers can be associated with one or more rules which define configuration parameters. These rules may be inherited by machines through both the physical and logical relationships of the machines in the computer network. This centralized administration of the computer network simplifies the task of configuring and monitoring the network. All machines in the computer network also can be configured or monitored simultaneously.

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Newton, MA, United States of America

Bret Harsham