Prosodic Parameter Manipulation in TTS generated speech for Controlled Speech Generation

TL;DR

This paper presents a method for manipulating prosodic parameters in TTS systems to produce more natural and expressive speech by aligning synthesized speech with human prosody.

Contribution

It introduces a framework for precise prosodic parameter adjustment in TTS, improving naturalness and expressiveness of generated speech.

Findings

Prosodic manipulation enhances speech naturalness.

Method achieves closer alignment with human speech patterns.

Framework is effective for controlled speech generation.

Abstract

This paper explores the manipulation of prosodic parameters in Text-to-Speech (TTS) systems to achieve controlled speech generation. By leveraging advanced speech processing techniques, we compare TTS-generated audio with human-recorded speech to analyze differences in pitch, duration, and energy. Key features are extracted using tools like PyWorld and Librosa, which are then adjusted to align with the prosodic characteristics of natural human speech. The modified features undergo synthesis, producing enhanced TTS outputs that more closely mirror the natural prosody of human speech. This approach aims to enhance the naturalness and expressiveness of TTS systems by providing a framework for precise prosodic parameter adjustments. Our methodology involves feature extraction, prosodic manipulation, and synthesis, followed by comprehensive evaluations to ensure consistency with human speech patterns. The findings demonstrate the feasibility and effectiveness of prosodic parameter manipulation for controlled speech generation, highlighting its potential to significantly improve TTS applications.