Assessing the Naturalness of Text-to-Speech Models for Brazilian Portuguese NPC Dialogue - Ferro Filho, Alexandre Costa; Sousa, Rafael Teixeira; Rosa, Augusto Seben da; Mendes, Leticia Lima; Pinto, Paula Leandra Loeblein; Galvão Filho, Arlindo Rodrigues (Anais do Simpósio de Realidade Virtual e Aumentada (SVR), 2025)
Believable Non-Player Character (NPC) voices are critical for creating immersive experiences in Virtual Reality (VR). However, traditional voice acting is costly and lacks scalability for extensive dialogues and localization, particularly for languages like Brazilian Portuguese. While Text-to-Speech (TTS) offers a viable alternative, there is a lack of systematic evaluation of modern models’ perceptual naturalness when generating domain-specific NPC dialogues in Portuguese. This paper addresses this gap by conducting a subjective evaluation of five State-of-the-Art TTS models: XTTS, Parler TTS, F5-TTS, Fish Speech, and Orpheus. Two test sets were created by translating dialogues from the LIGHT and CHiME-6 datasets. The naturalness of the synthesized audio was assessed through a Mean Opinion Score (MOS) user study with 13 native speakers. Results indicate moderate overall naturalness (average MOS 3.29), with Parler TTS and XTTS emerging as top performers (MOS 3.53). These findings provide a benchmark for developers creating localized VR content and highlight that achieving truly expressive NPC voices remains a significant research challenge.