# Increase Apparent Public Speaking Fluency By Speech Augmentation

## TL;DR

This paper introduces a speech augmentation system that enhances non-professional speakers' fluency by manipulating disfluencies, resulting in more confident and professional-like speech to improve listener engagement.

## Contribution

It presents a novel speech stream manipulation method that reduces disfluencies and silences, improving speech fluency without requiring professional training.

## Key findings

- Significant increase in speech fluency metrics
- Reduction in filler words and long pauses
- Enhanced perceived confidence in speech

## Abstract

Fluent and confident speech is desirable to every speaker. But professional speech delivering requires a great deal of experience and practice. In this paper, we propose a speech stream manipulation system which can help non-professional speakers to produce fluent, professional-like speech content, in turn contributing towards better listener engagement and comprehension. We propose to achieve this task by manipulating the disfluencies in human speech, like the sounds 'uh' and 'um', the filler words and awkward long silences. Given any unrehearsed speech we segment and silence the filled pauses and doctor the duration of imposed silence as well as other long pauses ('disfluent') by a predictive model learned using professional speech dataset. Finally, we output a audio stream in which speaker sounds more fluent, confident and practiced compared to the original speech he/she recorded. According to our quantitative evaluation, we significantly increase the fluency of speech by reducing rate of pauses and fillers.