Abstract: In various examples, techniques for accelerating inference in text and speech processing for conversational AI systems and applications is described herein. Systems and methods are disclosed that use one or more techniques, such as token merging, in order to reduce a number of tokens processed by one or more machine learning models. For instance, the machine learning model(s) may process text and, based at least on the processing, generate scores (e.g., attention scores) indicating relationships between tokens associated with the text. The machine learning model(s) may then use the scores to merge at least one pair of the tokens. As described herein, the merging may reduce the overall number of tokens associated with the text while still maintaining the same semantic meaning as the original text. Next, the machine learning model(s) may process the reduce number of tokens in order to determine an output associated with the text.

Abstract: Approaches presented herein provide systems and methods for generating three-dimensional (3D) content with fine grained emotions and character traits. A set of classifiers may be used to identify emotions and character traits from an input provided by a user. Each of the classifiers in the set of classifiers may use a set of seed words that is expanded through methods including manual collection, synonym extension, and/or word alignment. An input may then be evaluated for indications of emotion and/or character traits, such as by identifying certain words or phrases present within the input. Output vectors associated with the identified emotion and/or character traits may then be provided to different generative models to adjust content, such as modifications to output audio or facial expressions for digital character representations.

Abstract: Apparatuses, systems, and techniques to translate a text string. In at least one embodiment, a text string is translated by at least, for example, using one or more neural networks to determine a length of a translated text string before a text string is to be translated.

Abstract: Apparatuses, systems, and techniques to train one or more neural networks based, at least in part on, medical imaging data and clinical metadata or inference using one or more neural networks trained as such. In at least one embodiment, one or more circuits to train one or more neural network to predict a treatment for a patient suspected to have or confirmed to have COVID-19 based, at least in part on, medical imaging data and clinical metadata.