Automated assistants that accommodate multiple age groups and/or vocabulary levels
First Claim
1. A method implemented using one or more processors, comprising:
- receiving, at one or more input components of one or more client devices, a vocal utterance from a user;
applying data indicative of the vocal utterance across a trained machine learning model to generate output;
determine, based on the output, that the user falls into a predetermined age group;
selecting, from a plurality of candidate query understanding models, a given query understanding model that is associated with the predetermined age group;
determining an intent of the user using the given query understanding model;
determining, based on the predetermined age group, that the intent of the user is resolvable;
resolving the user'"'"'s intent to generate responsive data; and
outputting, at one or more output components of one or more of the client devices, the responsive data.
1 Assignment
0 Petitions
Accused Products
Abstract
Techniques are described herein for enabling an automated assistant to adjust its behavior depending on a detected age range and/or “vocabulary level” of a user who is engaging with the automated assistant. In various implementations, data indicative of a user'"'"'s utterance may be used to estimate one or more of the user'"'"'s age range and/or vocabulary level. The estimated age range/vocabulary level may be used to influence various aspects of a data processing pipeline employed by an automated assistant. In various implementations, aspects of the data processing pipeline that may be influenced by the user'"'"'s age range/vocabulary level may include one or more of automated assistant invocation, speech-to-text (“STT”) processing, intent matching, intent resolution (or fulfillment), natural language generation, and/or text-to-speech (“TTS”) processing. In some implementations, one or more tolerance thresholds associated with one or more of these aspects, such as grammatical tolerances, vocabularic tolerances, etc., may be adjusted.
-
Citations
20 Claims
-
1. A method implemented using one or more processors, comprising:
-
receiving, at one or more input components of one or more client devices, a vocal utterance from a user; applying data indicative of the vocal utterance across a trained machine learning model to generate output; determine, based on the output, that the user falls into a predetermined age group; selecting, from a plurality of candidate query understanding models, a given query understanding model that is associated with the predetermined age group; determining an intent of the user using the given query understanding model; determining, based on the predetermined age group, that the intent of the user is resolvable; resolving the user'"'"'s intent to generate responsive data; and outputting, at one or more output components of one or more of the client devices, the responsive data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A method implemented using one or more processors, comprising:
-
receiving, at one or more input components of one or more client devices, a vocal utterance from a user; applying data indicative of the vocal utterance across a trained machine learning model to generate output; determining, based on the output, that the user falls into a given vocabulary level of a plurality of predetermined vocabulary levels; selecting, from a plurality of candidate query understanding models, a given query understanding model that is associated with the given vocabulary level; determining an intent of the user using the given query understanding model; determining, based on the given vocabulary level, that the intent of the user is resolvable; resolving the user'"'"'s intent to generate responsive data; and outputting, at one or more output components of one or more of the client devices, the responsive data. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
-
-
17. A system comprising one or more processors and memory operably coupled with the one or more processors, wherein the memory stores instructions that, in response to execution of the instructions by one or more processors, cause the one or more processors to perform the following operations:
-
receiving, at one or more input components of one or more client devices, a vocal utterance from a user; applying data indicative of the vocal utterance across a trained machine learning model to generate output; determine, based on the output, that the user falls into a predetermined age group; selecting, from a plurality of candidate query understanding models, a given query understanding model that is associated with the predetermined age group; determining an intent of the user using the given query understanding model; determining, based on the predetermined age group, that the intent of the user is resolvable; resolving the user'"'"'s intent to generate responsive data; and outputting, at one or more output components of one or more of the client devices, the responsive data. - View Dependent Claims (18, 19, 20)
-
Specification