What does it take to get state of the art in simultaneous speech-to-speech translation?

TL;DR

This paper analyzes latency issues in simultaneous speech-to-speech translation models, identifying causes of latency spikes and proposing strategies to reduce them, thereby improving real-time translation performance.

Contribution

It provides a systematic analysis of latency spikes and introduces methods to minimize them through input management and parameter tuning.

Findings

Latency spikes are caused by hallucination effects.

Careful input management reduces latency spikes.

Parameter adjustments significantly improve latency performance.

Abstract

This paper presents an in-depth analysis of the latency characteristics observed in simultaneous speech-to-speech model's performance, particularly focusing on hallucination-induced latency spikes. By systematically experimenting with various input parameters and conditions, we propose methods to minimize latency spikes and improve overall performance. The findings suggest that a combination of careful input management and strategic parameter adjustments can significantly enhance speech-to-speech model's latency behavior.