September 23, 2025ComputersOpen Access

Benchmarking the Responsiveness of Open-Source Text-to-Speech Systems

View Full Paper

Ask AI

Bookmark

Authors

Discussion

This evaluation captures responsiveness and latency in 13 open-source text-to-speech models, highlighting reproducibility.

Responsiveness is crucial for real-time applications, unlike typical quality metrics for speech systems.
The benchmark reveals variability in latency, with some TTS models offering near-instant output while others lag.
Our open-source framework incorporates intelligibility and latency metrics for accurate, reproducible comparisons.
This groundwork supports further comprehensive assessments of TTS systems, combining responsiveness with quality.

Dinh et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark

September 23, 2025ComputersOpen Access

View Full Paper

Ask AI

Bookmark

Authors

This evaluation captures responsiveness and latency in 13 open-source text-to-speech models, highlighting reproducibility.

Responsiveness is crucial for real-time applications, unlike typical quality metrics for speech systems.
The benchmark reveals variability in latency, with some TTS models offering near-instant output while others lag.
Our open-source framework incorporates intelligibility and latency metrics for accurate, reproducible comparisons.
This groundwork supports further comprehensive assessments of TTS systems, combining responsiveness with quality.

Dinh et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark