Text-to-Speech Synthesis via Iterative User Feedback
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Solution Overview
Problem
Automated text-to-speech (TTS) systems face challenges in generating natural-sounding speech, particularly for long portions of text, as they do not adequately account for variations in human voice over extended periods, leading to unnatural speech output.
Innovation Solution
A user-feedback iterative method is introduced, where preliminary TTS results are displayed to users for editing, allowing them to alter acoustic features and phonetic units, which are then incorporated into subsequent processing passes to improve the quality of the speech synthesis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated text-to-speech systems process long portions of text, then productivity is improved, but the naturalness of speech output deteriorates due to inability to account for voice variations over extended periods
Solution Approach 1:
The speech synthesis process is divided into multiple passes or segments. The system processes long text portions by breaking them into smaller units, applying different processing strategies to each segment while maintaining overall coherence. This allows the system to handle extended text while preserving natural speech characteristics in each segment.
Solution Approach 2:
The system dynamically adjusts processing parameters based on the position and context within the text. As the synthesis progresses through long portions of text, the system adapts acoustic features, timing, and other parameters to simulate natural voice variations that occur during extended human speech, rather than maintaining static parameters throughout.
2Device complexity
If traditional text-to-speech systems are used, then device complexity is reduced, but the quality and naturalness of speech output deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms where the output of one processing pass informs subsequent passes. By analyzing the generated speech and comparing it against natural speech patterns, the system iteratively refines acoustic features, timing, and other parameters to improve naturalness without requiring completely complex system architecture.
Solution Approach 2:
The system performs preliminary processing and analysis before final speech generation. By pre-processing the text, identifying key features, and preparing acoustic parameters in advance, the system improves speech quality through multiple refinement passes while maintaining manageable device complexity through structured preprocessing steps.
Data Source
AI summary
A text-to-speech (TTS) processing system may be configured for iterative processing. Speech units for unit selection may be tagged according to extra segmental features, such as emotional features, dramatic features, etc. Preliminary TTS results based on input text may be provided to a user through a user interface. The user may offer corrections to the preliminary results. Those corrections may correspond to the extra segmental features. The user corrections may then be input into the TTS system along with the input text to provide refined TTS results. This process may be repeated iteratively to obtain desired TTS results.