Answer: Text-to-speech technology, also known as TTS, is a technology that converts written text into spoken words. It allows computers and devices to audibly communicate information to users.

Answer: Basic synthesis text-to-speech works by using pre-recorded speech fragments, also known as phonemes, to construct spoken words and sentences. These phonemes are stored in a database and are combined to form the desired speech output.

Answer: Basic synthesis text-to-speech often sounds robotic and lacks naturalness and expressiveness. It may have difficulty pronouncing certain words or phrases accurately, leading to a less immersive and engaging user experience.

Answer: Text-to-speech technology has evolved significantly over the years. Advances in machine learning and artificial intelligence have led to the development of more sophisticated synthesis techniques, resulting in more natural and human-like voices.

Answer: Neural networks play a crucial role in modern text-to-speech technology. Deep learning models, such as WaveNet and Tacotron, utilize neural networks to generate speech waveforms and learn the patterns and nuances of human speech, resulting in more natural and expressive voices.

Answer: Natural human-like voices in text-to-speech technology enhance user experience by making the interaction more engaging and immersive. They enable a more natural and intuitive communication between humans and machines, allowing for better accessibility and usability.