Human Voice Recording Retrieval for Credible Query Responses
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Solution Overview
Problem
Existing voice-based assistant technologies rely on text-to-speech processing for responses, which may lack credibility and compellingness compared to human voice recordings.
Innovation Solution
A system that stores and ranks prerecorded human voice recordings based on credibility measures, using objective and subjective attributes to provide responsive audio recordings to user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If text-to-speech processing is used to generate voice responses, then automation and efficiency are improved, but credibility and compellingness deteriorate
Solution Approach 1:
The patent applies the copying principle by creating synthetic voice recordings that replicate the characteristics, tone, and style of expert human speakers. Instead of using actual human recordings for all responses, the system generates convincing copies of expert voices through AI voice synthesis, maintaining credibility while enabling automated generation of unlimited responses.
Solution Approach 2:
The system employs parameter changes by dynamically adjusting voice characteristics such as pitch, tone, speaking rate, and emotional inflection to match the desired expert persona. This allows the automated system to produce voice responses that sound natural and credible by modifying acoustic parameters to mimic human speech patterns.
2Reliability
If a large corpus of human voice recordings is stored and searched, then credibility and quality are improved, but device complexity and storage requirements worsen
Solution Approach 1:
The patent applies segmentation by dividing the voice corpus into organized categories based on expertise domains, speaker characteristics, and topic relevance. This structured segmentation enables efficient retrieval of appropriate voice recordings without requiring the system to manage a monolithic, overly complex database, reducing operational complexity while maintaining high quality.
Solution Approach 2:
The system introduces an intermediary AI voice synthesis layer that acts as a mediator between the text response generation and the final voice output. This intermediary can either select from the human voice corpus or generate synthetic voice recordings, simplifying the overall system architecture by providing a flexible intermediate step that reduces the need for exhaustive human recording collections.
3Reliability
If voice recordings are ranked by credibility measures, then response quality is improved, but processing time and computational resources worsen
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing credibility scores for each voice recording based on speaker expertise, recording quality, and relevance metrics. These pre-computed credibility measures are saved in the database alongside the voice recordings, allowing the system to quickly retrieve and rank recordings without performing complex credibility assessments in real-time, thus reducing processing time.
Solution Approach 2:
The system applies local quality by optimizing the credibility ranking process for specific query contexts. Instead of uniformly processing all recordings with equal computational resources, the system adjusts the ranking depth and criteria based on the specific query requirements, allowing faster processing for simple queries while maintaining high credibility standards for complex topics.
Data Source
AI summary
Implementations are provided for providing responsive audio recordings to user queries that are prerecorded by human beings, rather than generated automatically using speech synthesis processing. In various implementations, a query provided by a user at an input component of a computing device may be used to search a corpus of voice recordings. From the searching, a plurality of candidate responsive voice recordings may be identified and ranked based on measures of credibility associated with speakers that created the candidate responsive voice recordings. Based on the ranking, one or more of the plurality of candidate responsive voice recordings may be provided for presentation to the user at an output component of the same computing device or a different computing device.