Arbitrator for Voice Command Fulfillment Using Taste Profiles

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing human-machine interfaces struggle to process complex voice-based commands effectively, particularly in media content management, due to limitations in natural language processing systems that often provide a single output with high confidence, leading to incorrect interpretations and wasted processing resources.

Innovation Solution

A natural language processing system that generates multiple possible outputs at various stages of utterance processing, allowing for a greater chance of correct fulfillment of user requests through an automated speech recognizer, natural language understanding system, and fulfillment manager that utilize confidence scores and taste profiles to select the appropriate fulfillment strategy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a natural language processing system provides a single high-confidence output at each processing stage, then the system operates with simpler decision-making logic, but the accuracy of fulfilling user requests decreases due to potential incorrect interpretations

Engineering Contradiction:

Improveaccuracy of request fulfillmentVSAvoidcomplexity of decision-making logic

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments the natural language processing into multiple independent stages (speech recognition, natural language understanding, fulfillment strategy selection), where each stage generates multiple candidate outputs rather than a single deterministic result. This segmentation allows each component to operate independently while contributing to the overall accuracy through cumulative confidence assessment.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs excessive action by generating more outputs than traditionally required at each processing stage. Instead of selecting a single transcription or meaning representation, the system preserves multiple candidates with associated confidence scores, allowing downstream components to benefit from the expanded search space and make more informed decisions.

Inventive Principle:

Principle #16Partial or excessive action

2Reliability

If multiple possible outputs are generated at each processing stage, then the accuracy of request fulfillment improves, but the processing resources are consumed more heavily

Engineering Contradiction:

Improveaccuracy of request fulfillmentVSAvoidprocessing resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary action by pre-computing and storing multiple candidate outputs with confidence scores at each processing stage. The automated speech recognizer pre-generates multiple transcriptions, and the natural language understanding system pre-computes multiple meaning representations. This preliminary computation allows the fulfillment manager to efficiently select the best strategy without performing computationally intensive real-time analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms where confidence scores from each processing stage are fed back to influence subsequent stage processing. The fulfillment manager uses confidence scores from speech recognition and natural language understanding to weight and evaluate different fulfillment strategies, allowing the system to focus computational resources on the most promising candidates rather than uniformly processing all possibilities.

Inventive Principle:

Principle #23Feedback

3Speed

If a single fulfillment strategy is selected based on high-confidence output, then the system responds faster to user requests, but the likelihood of incorrect fulfillment increases

Engineering Contradiction:

Improveresponse time to user requestsVSAvoidcorrectness of fulfillment

Core Design Contradiction:

SpeedVSReliability

Solution Approach 1:

The system applies dynamics by making the fulfillment strategy selection adaptive rather than static. The arbitrator dynamically evaluates multiple fulfillment strategies based on real-time confidence scores from previous processing stages and user-specific taste profiles. This dynamic approach allows the system to quickly select the most appropriate strategy while maintaining high accuracy through confidence-based weighting and profile-driven personalization.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20250118295A1Systems and Methods for Improving Fulfillment of Media Content Related Requests via Utterance-Based Human-Machine Interfaces

Publication Date: 2025.04.10 SPOTIFY

AI summary

Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.