Voice Synthesis Sound Model Matching for User Attributes
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Solution Overview
Problem
Current voice synthesis systems fail to recommend suitable sound models based on user preferences or attributes, leading to suboptimal voice synthesis experiences, as they do not consider the appropriateness of sound models for specific content.
Innovation Solution
A voice synthesis method and device that determine a recommended sound model by matching user attributes with sound model attributes and then recommend content based on the sound model attributes, enabling voice synthesis using the recommended sound model to produce a synthesized voice file.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually select sound models from available options, then users can choose from a variety of sound models with different tone and accent features, but the system cannot ensure that the selected sound model is appropriate for the user's preferences or the content being synthesized
Solution Approach 1:
The system automatically performs sound model selection and content recommendation without requiring user intervention. The matching module autonomously analyzes user attributes and content characteristics to recommend the most suitable sound model, eliminating the need for users to manually evaluate and select from multiple sound models while ensuring accurate matching.
Solution Approach 2:
The patent replaces the manual mechanical selection process with an automated computational matching system. The matching module uses attribute comparison algorithms to automatically determine the optimal sound model based on user attributes and content characteristics, substituting human judgment with systematic automated analysis.
2Adaptability or versatility
If the system provides multiple sound models with different characteristics, then users have more options for voice synthesis, but it becomes difficult to ensure that the appropriate sound model is used for each specific content type
Solution Approach 1:
The matching module serves as an intermediary between the diverse sound models and the content to be synthesized. It analyzes both the sound model attributes and content characteristics, then recommends the most appropriate match, simplifying the interaction between users and the complex sound model library while ensuring optimal pairing.
Solution Approach 2:
The system changes the approach from manual selection based on subjective preferences to automated selection based on objective attribute parameters. By comparing specific attributes (tone features, accent characteristics, content type) between sound models and content, the system objectively determines the best match regardless of the variety of available sound models.
3Measurement precision
If the system automatically recommends sound models based on user attributes, then the matching accuracy improves, but the system complexity increases due to the need for attribute matching operations
Solution Approach 1:
The matching module performs multiple functions simultaneously: it analyzes user attributes, evaluates sound model characteristics, assesses content properties, and generates recommendations. This multi-functional approach consolidates what would otherwise require separate systems into a single integrated component, achieving high recommendation accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
A voice synthesis method is provided. The method includes: determining a recommended sound model by performing a first matching operation on a user attribute and a sound model attribute of the sound model; determining a recommended content by performing a second matching operation on a sound model attribute of the recommended sound model and a content attribute of the content; and performing a voice synthesis on the recommended content by using the recommended sound model, to obtain a synthesized voice file.