Voice-Enabled Recipe Selection with Automatic Ingredient Sizing

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Solution Overview

Problem

Existing systems for preparing recipes using voice commands are inefficient as they require users to manually select and order ingredient sizes, which is time-consuming and resource-intensive.

Innovation Solution

A voice-enabled recipe selection system that detects the intention to order ingredients from a voice command and automatically adds the necessary items to an online order, determining suitable sizes and quantities based on the recipe requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If users manually select and order each ingredient size for voice commands, then the system can accurately fulfill recipe requirements, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:
Improveingredient quantity accuracyVSAvoidorder preparation time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system pre-processes recipes to extract ingredient information and pre-configures available item sizes in the database before user interaction. When a voice command is received, the system already has the recipe requirements and item catalog ready, enabling rapid matching and selection without manual user input for each ingredient size.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system automatically determines the appropriate item size and quantity based on the recipe requirements and available inventory, without requiring users to manually specify each parameter. The system self-services by inferring the needed information from the recipe data and system catalog, reducing user burden while maintaining accuracy.

Inventive Principle:
Principle #25Self-service

2Measurement precision

If users manually specify each ingredient size in voice commands, then the system can ensure correct ingredient quantities, but computational resources are excessively consumed

Engineering Contradiction:
Improveingredient quantity accuracyVSAvoidcomputational resource consumption
Core Design Contradiction:
Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system performs pre-processing of recipes to extract and structure ingredient information before runtime. The item catalog with available sizes is pre-configured in the database. This preliminary preparation eliminates the need for complex real-time computations when processing voice commands, significantly reducing computational resource consumption while maintaining accurate ingredient quantity determination.

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If the system processes each ingredient size selection individually, then it can maintain high accuracy in ingredient quantities, but the overall processing speed decreases

Engineering Contradiction:
Improveingredient quantity accuracyVSAvoidprocessing speed
Core Design Contradiction:
Measurement precisionVSSpeed

Solution Approach 1:

The system merges the processing of multiple ingredient size selections into a single automated workflow triggered by one voice command. Instead of handling each ingredient separately with manual user input, the system combines all ingredient requirements from the pre-processed recipe and automatically matches them with available item sizes in batch, maintaining accuracy while significantly improving processing speed.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentUS12277593B2Voice-enabled recipe selection
Publication Date: 2025.04.15 WALMART APOLLO LLC
  • US12277593B2 patent drawing
  • US12277593B2 patent drawing
  • US12277593B2 patent drawing

AI summary

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed configured to run on the one or more processors, cause the one or more processors to and perform operations: receiving a command from a user; transforming, using a trained machined learning model, the command by detecting an intent to add one or more recipe ingredients; determining a recipe from a set of recipes; determining one or more items and one or more quantities or sizes of the one or more items; selecting a respective quantity or size from quantities or sizes of available items of the one or more items, wherein the respective quantity or size, as selected, is overruled when a different quantity or size preference is indicated by the user; and automatically adding to the shopping cart the one or more items. Other embodiments are described.