Amazon Technologies, Inc.

Alexander Thomas Loeb

Vikram Kumar Gundeti

Michael F Schwartz

Rongzhou Shen

Bo Li

Leopold Bushkin

Yaser Khan

Munir Mahmood

Shemyla Anwar

Mohammed Arif

Edward Page Foyle

Chenlei Guo

Xing Fan

Kerry Hammil

Archit Jain

Hyungseo Park

Robert O'Neal Copeland

Devices and techniques are generally described for arbitration between LLM-based and intent-based natural language processing flows. In various examples, an automatic speech recognition (ASR) component may generate first ASR output data representing the first natural language input. A first machine learning model may select an LLM-based natural language processing flow. The first machine learning model may be trained to select between at least the LLM-based and non-LLM-based natural language processing flows. The first ASR output data may be processed using the LLM-based processing flow. The LLM-based processing flow may generate first executable data.

Language model arbitration for natural language processing

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input corresponding to more than one user command. The NLP system may respond to a first command, of the natural language input, using a TTS voice of a first NLP system assistant. The NLP system may respond to a second command, of the natural language input, using a TTS voice of a second NLP system assistant.

Multi-assistant natural language input processing

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input from a device. The NLP system may also receive one or more signals representing one or more assistants to be implemented with respect to the natural language input. The NLP system may intelligently select an assistant to be invoked with respect to the natural language input. Once the assistant is selected, the NLP system may cause content, output to a user, to have characteristics specific to the assistant.

Multi-assistant natural language input processing to determine a voice model for synthesized speech

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Lynnwood, WA, United States of America

Alexander Thomas Loeb