arXiv:2606.14922v1 Announce Type: cross Abstract: For the last couple of years, the field of speech synthesis has improved dramatically thanks to deep learning. There are more and more deep learning-based TTS systems developed to make it possible to produce voices with high intelligibility and naturalness. Meanwhile, controlling the expressiveness is yet a big deal, generating speech in different styles or manners has received a lot of attention from community recently. This paper aims to give our solutions to deal with the task emotional speech synthesis (ESS) at VLSP 2022 which allows to gen
Deep learning advancements are rapidly pushing the boundaries of speech synthesis, making highly natural and expressive AI voices increasingly achievable.
Improved emotional speech synthesis is a key enabler for more natural human-computer interaction, enhancing the utility and adoption of AI in various applications.
The ability of AI systems to convey nuanced emotions through speech will improve, moving beyond purely intelligible but flat vocal outputs.
- · AI assistants
- · Customer service platforms
- · Content creation
- · Gaming industry
- · Monotone voice synthesis providers
- · Companies relying on limited voice AI
More human-like AI voices will become common in daily interactions and digital media.
Public perception of AI 'personhood' or sentience may subtly shift as interactions become more emotionally resonant.
The development of sophisticated emotional AI could lead to new ethical debates regarding manipulation and authenticity in digital communications.
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