Interactive Text-to-Speech Adaptation for User-Controlled Pacing
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Solution Overview
Problem
Conventional text-to-speech (TTS) systems lack interactivity and fail to adjust speech characteristics naturally, leading to reduced user engagement and comprehension, particularly in human learning contexts.
Innovation Solution
A method and system that adapt speech synthesis by using the position and motion of a tracking operation, such as a cursor, to adjust speech pace and characteristics based on user interaction with displayed text, integrating machine learning to enhance the naturalness and interactivity of synthesized speech.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional TTS systems synthesize speech at a fixed canonical speech-pace, then the system maintains simple and stable operation, but user engagement and comprehension are reduced due to lack of interactivity and naturalness
Solution Approach 1:
The TTS system dynamically adjusts speech characteristics based on real-time tracking operation data. The speech-pace, pitch, and volume are no longer fixed but adapt continuously according to user interaction patterns detected through tracking operations on the display device, making the system dynamic and responsive to user needs
Solution Approach 2:
The system implements feedback loops where tracking operation position and motion data are continuously monitored and fed back to the speech synthesis engine. This feedback mechanism allows the TTS system to adjust its output in real-time based on user engagement patterns, improving adaptability while maintaining manageable complexity through structured feedback processing
2Adaptability or versatility
If the TTS system processes the entire text segment at once, then the speech synthesis is efficient and continuous, but the system cannot adapt to user-controlled pacing and comprehension needs
Solution Approach 1:
The text segment is divided into smaller portions based on tracking operation positions. Instead of processing the entire text at once, the system segments the text into manageable chunks that can be synthesized and delivered at user-controlled paces, allowing for better adaptation while maintaining reasonable processing efficiency through targeted synthesis of only relevant segments
Solution Approach 2:
The speech synthesis process is made dynamic by adjusting the processing pace according to user interaction. The system can accelerate or decelerate synthesis of different text portions based on tracking motion data, enabling user-controlled pacing while maintaining overall productivity through intelligent resource allocation to actively engaged text segments
3Adaptability or versatility
If the TTS system maintains consistent speech characteristics throughout the text, then the synthesis process is simple and reliable, but the speech lacks natural variation and user engagement
Solution Approach 1:
Different portions of the text segment receive different speech characteristics based on local user interaction patterns. The system applies local quality adjustments where pitch, pace, and volume vary according to the specific tracking operations detected in different text regions, creating natural speech variation while maintaining reliability through consistent application of adaptation rules
Solution Approach 2:
The system uses feedback from tracking operation patterns to dynamically adjust speech characteristics. By monitoring user engagement through tracking data and feeding this information back to the synthesis engine, the system achieves natural speech variation that responds to user needs while maintaining reliability through structured feedback-based adjustment mechanisms
Data Source
AI summary
A method and system is disclosed for adapting speech synthesis according to user-interface input. While synthesizing speech from a text segment with a text-to-speech (TTS) system and concurrently displaying the text segment in a display device, the system may receive tracking operation input tracking a portion of text undergoing synthesis and identifying a context portion of the text for which prior-synthesized speech has been synthesized at a canonical speech-pace. The tracking information may be used to adjust a speech-pace of TTS synthesis of the portion from the canonical speech-pace to an adapted speech-pace, and speech characteristics of synthesized speech of the portion may be adapted by applying both the adapted speech-pace and synthesized speech characteristics of the prior-synthesized speech of the context portion to TTS synthesis processing of the portion. The synthesized speech of the identified portion may be output at the adapted speech-pace and with the adapted speech characteristics.