Text-to-speech task scheduling with progress timer prioritization
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Solution Overview
Problem
Text-to-speech (TTS) systems experience delays and interruptions due to inefficient resource allocation and task prioritization, leading to underrun situations where audio playback pauses, disrupting the user experience.
Innovation Solution
A system that schedules TTS tasks using a progress timer to measure how long a task has been synthesized, prioritizing tasks based on their progress time to reduce delays and interruptions, ensuring continuous speech delivery by dynamically reallocating computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing resources are allocated to multiple TTS tasks simultaneously, then system productivity increases, but task completion time increases causing delays and underrun situations
Solution Approach 1:
The patent implements continuous monitoring of synthesis progress timers for all active TTS tasks, ensuring that resource allocation decisions are made continuously rather than periodically. This allows the system to maintain continuous useful action by always having the most critical tasks (those closest to underrun) being processed, preventing gaps in speech output while efficiently utilizing computing resources across multiple tasks
Solution Approach 2:
The system employs feedback mechanisms by continuously measuring synthesis progress against time thresholds and using this information to dynamically adjust resource allocation. The progress timer provides real-time feedback on each task's status, enabling the scheduler to reallocate resources from tasks that are progressing adequately to tasks that are at risk of underrun, thus maintaining both high productivity and timely completion
2Speed
If computing resources are dedicated to a single TTS task, then task completion speed increases, but system versatility decreases due to inability to handle multiple tasks
Solution Approach 1:
The patent implements dynamic resource allocation where the amount of computing resources dedicated to each TTS task changes over time based on real-time progress monitoring. Tasks that are close to completion or progressing rapidly receive fewer resources, while tasks approaching underrun thresholds receive increased resources. This dynamic adjustment allows the system to maintain high completion speeds for individual tasks while simultaneously handling multiple tasks with varying resource needs
Solution Approach 2:
The system applies local quality by allocating different levels of computing resources to different TTS tasks based on their specific needs and progress states. Rather than uniform resource distribution, each task receives a customized resource allocation proportional to its urgency and progress, enabling the system to optimize completion speed for each task locally while maintaining overall system versatility
3Reliability
If resource reallocation frequency increases, then speech continuity improves, but system complexity increases due to frequent scheduling decisions
Solution Approach 1:
The patent implements periodic resource reallocation based on synthesized time thresholds rather than continuous or event-driven reallocation. The system checks progress at regular intervals defined by time thresholds, reallocating resources when tasks approach critical points. This periodic approach maintains speech continuity by ensuring timely interventions while avoiding the excessive complexity of continuous monitoring and decision-making
Solution Approach 2:
The system manages complexity by changing key parameters (resource allocation levels) only when necessary, based on progress threshold evaluations. Rather than continuously adjusting resources, the system maintains stable allocations until tasks approach underrun conditions, at which point parameter changes are made to restore continuity. This selective parameter change approach maintains reliability while limiting system complexity
Data Source
AI summary
To prioritize the processing text-to-speech (TTS) tasks, a TTS system may determine, for each task, an amount of time prior to the task reaching underrun, that is the time before the synthesized speech output to a user catches up to the time since a TTS task was originated. The TTS system may also prioritize tasks to reduce the amount of time between when a user submits a TTS request and when results are delivered to the user. When prioritizing tasks, such as allocating resources to existing tasks or accepting new tasks, the TTS system may prioritize tasks with the lowest amount of time prior to underrun and/or tasks with the longest time prior to delivery of first results.