Amazon Technologies, Inc.

Nalledath P Vinodkrishnan

Ramakanthachary S Gottumukkala

Shaun M Vickers

Vaidyanathan Puthucode Krishnamoorthy

Charles Conroy Moore

Sethuraman Ramachandran

Oleg Rokhlenko

Ankit Agrawal

Julia Reinspach

Costantino Vlachos

Guy Michaeli

Swayam Bhardwaj

Giovanni Clemente

Prathap Ramachandra

Liu Yang

Jingqian Zhao

Wenbo Yan

Ponnu Jacob

Phillip Segel

Ruiqi Luo

Charlotte Alizerine Dzialo

Uday Kumar Kollu

Adriano Devillaine

Adam Kalman

Aravindhan Rathakrishnan

Saravana Prasad Stalin

Krupal Maddipati

Branden Nicholas Vandermoon

Meng Xie

Mateusz Haligowski

Mohammad Alnuaimat

Pablo Alberto De Stefani Casanova

Nader Ali Syed Shirazie

A request including audio data is received from a voice-enabled device. A string of phonemes present in the utterance is determined through speech recognition. At a later time, a subsequent user input corresponding to the request may be received, in which the user input is associated with one or more text keywords. The subsequent user input may be obtained in response to an active request. Alternatively, feedback may not be actively elicited, but rather collected passively. However it is obtained, the one or more keywords associated with the subsequent user input may be associated with the string of phonemes to indicate that the user is saying or mean those words when they product that string of phonemes. A user-specific speech recognition key for the user account is then updated to associate the string of phonemes with these words. A general speech recognition model can also be trained using the association.

Speech recognition through disambiguation feedback

In various embodiments, a voice command is associated with a plurality of processing steps to be performed. The plurality of processing steps may include analysis of audio data using automatic speech recognition, generating and selecting a search query from the utterance text, and conducting a search of database of items using a search query. The plurality of processing steps may include additional or different steps, depending on the type of the request. In performing one or more of these processing steps, an error or ambiguity may be detected. An error or ambiguity may either halt the processing step or create more than one path of actions. A model may be used to determine if and how to request additional user input to attempt to resolve the error or ambiguity. The voice-enabled device or a second client device is then causing to output a request for the additional user input.

Triggering voice control disambiguation

A speech processing system uses contextual data to determine the specific domains, subdomains, and applications appropriate for taking action in response to spoken commands and other utterances. The system can use signals and other contextual data associated with an utterance, such as location signals, content catalog data, data regarding historical usage patterns, data regarding content visually presented on a display screen of a computing device when an utterance was made, other data, or some combination thereof.

Dynamic context-based routing of speech processing

This disclosure describes methods, apparatuses, and systems for providing visualizations of workflows. Data associated with successes and failures of individual components of workflows can be collected and aggregated to provide an overview of the operation of workflows, as well as allowing a software developer to troubleshoot operations of the workflow. Status indications of steps can be visualized in a graphical user interface (GUI), for example, and faults can be identified and presented in the GUI. By aggregating workflow data across hundreds, thousands, or even millions of workflows, a user can quickly determine the overall operations of the workflow, as well as areas of the workflow that may need improvement.

Process visualization platform

Growing community of inventors

Bellevue, WA, United States of America

Nalledath P Vinodkrishnan