  Text animation serves as an expressive medium, transforming static
communication into dynamic experiences by infusing words with motion to evoke
emotions, emphasize meanings, and construct compelling narratives. Crafting
animations that are semantically aware poses significant challenges, demanding
expertise in graphic design and animation. We present an automated text
animation scheme, termed "Dynamic Typography", which combines two challenging
tasks. It deforms letters to convey semantic meaning and infuses them with
vibrant movements based on user prompts. Our technique harnesses vector
graphics representations and an end-to-end optimization-based framework. This
framework employs neural displacement fields to convert letters into base
shapes and applies per-frame motion, encouraging coherence with the intended
textual concept. Shape preservation techniques and perceptual loss
regularization are employed to maintain legibility and structural integrity
throughout the animation process. We demonstrate the generalizability of our
approach across various text-to-video models and highlight the superiority of
our end-to-end methodology over baseline methods, which might comprise separate
tasks. Through quantitative and qualitative evaluations, we demonstrate the
effectiveness of our framework in generating coherent text animations that
faithfully interpret user prompts while maintaining readability. Our code is
available at: https://animate-your-word.github.io/demo/.
