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You're developing a system that translates spoken language into sign language animations. Which of the following losses would be MOST suitable for training the model to generate realistic and accurate sign language sequences from speech input?
Correct Answer: C
MSE loss ensures accurate joint positioning, while the temporal smoothness loss prevents jerky and unnatural movements. Cross-entropy is suitable for classification tasks, not continuous sequence generation. Cosine Similarity between embeddings might encourage general alignment, but doesn't guarantee accurate pose reproduction and Binary Cross entropy is only good for Binary Classification tasks.