Neural Voice Replication: Multispeaker Text-to-Speech Synthesizer

Voice replication, or cloning, is the ability to replicate an individual’s voice in real time, now it has achieved a significant breakthrough by the integration of deep learning technologies. This pioneering development holds vast potential across various industries, including personalization, entertainment, and accessibility. It enables the creation of extremely unidealistic voices that are indistinguishable from their human counterparts. This paper explores the recent advancements in real time voice replication through deep learning methods, showing its importance, challenges, and applications. The very extent of voice replication techniques has now undergone a noteworthy transformation, basically attributed to the adoption of deep learning methodologies such as neural text-to-speech (TTS) models, generative adversarial networks (GANs), and variational autoencoders (VAEs). By using substantially large datasets of target voices, these voice replication systems can generate synthesized speech closely resembling the source itself, hence making them invaluable tools for content creators and accessibility services. This ability of real-time voice replication has now unlocked numerous applications. Within the entertainment industry, actors, actresses, and individual artists can now utilize voice replication to create their own characters with unique artificial voices. This technology can also be utilized by other industries, like the gaming industry, where it can facilitate gamers with personalized and captivating experiences. In the field of assistive technologies, it holds the potential to provide a voice to individuals with speech impairments, offering them a better means of communication.