In Automatic Speech Recognition (ASR), scoring a beam of hypothesized sentences interpolates the score assigned by the language model with the encoder-decoder score used to create the beam, using a weight $\lambda$ tuned on a holdout set. Since most models prefer shorter sentences, ASR systems generally add a length factor, such as normalizing the probability by the number of characters in the hypothesis $|Y|_c$. The accompanying image contains a typical scoring function.