What is perplexity definition?

Perplexity is a mathematical measure used to evaluate the quality of a language model. It is a measurement of uncertainty or confusion in making predictions.

In natural language processing, perplexity is often used to measure how well a language model can predict the probability distribution of the next word in a sequence of words. A lower perplexity score indicates a better language model and better predictive performance.

Perplexity is calculated using the cross-entropy of the predicted and actual probability distributions of the language model for a given sequence of words. It is a mathematical formula that indicates how well a language model can predict the likelihood of the next word in a text sequence based on the previous words in the sequence.

Perplexity is used as a measure of the quality of language models in various applications, including speech recognition, machine translation, and text generation. It is a useful tool for evaluating the effectiveness of different language models and can help researchers and developers improve their models.