What is the difference between a language model and a speech recognition model?
A language model and a speech recognition model are both used in natural language processing but have different objectives.
A language model is trained to predict the probability of the next word in a sequence of words. The input to a language model is typically a sequence of words, and the output is the probability distribution over the vocabulary of words for the next word in the sequence.
On the other hand, a speech recognition model is used to transcribe spoken language into written text. The input to a speech recognition model is a sequence of audio samples, and the output is the corresponding sequence of words.
While a language model is concerned with predicting the next word given a sequence of words, a speech recognition model is concerned with mapping acoustic features of speech to written text.
