Google Inc.

David Joseph Weiss

Yuan Zhang

Jason Michael Baldridge

Daniel Gillick

Jason Riesa

Anton Bakalov

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating dependency parses for input text segments, which may be provided as inputs to a natural language processing system. One of the systems includes a first neural network comprising: one or more initial neural network layers configured to, for each token in an input text sequence: receive features for the token; and collectively process the features to generate an alternative representation of the features for use in determining a part of speech of the token in the input text sequence; and a dependency parsing neural network configured to: process the alternative representations of the features for the tokens in the input text sequence generated by the one or more initial neural network layers to generate a dependency parse of the input text sequence.

Generating dependency parses of text segments using neural networks

A method for identifying codemixed text includes receiving codemixed text and segmenting the codemixed text into a plurality of tokens. Each token includes at least one character and is delineated from any adjacent tokens by a space. For each token of the codemixed text, the method also includes extracting features from the token and predicting a probability distribution over possible languages for the token using a language identifier model configured to receive the extracted features from the token as feature inputs. The method also includes assigning a language to each token of the codemixed text by executing a greedy search on the probability distribution over the possible languages predicted for each respective token.

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Philadelphia, PA, United States of America

David Joseph Weiss