Statistical language model aims to estimate the probability distribution of various linguistic units such as words and sentences. Language models employ statistical estimation techniques using text. The most popular language models are N-grams models. These models are fundamental to a variety of language technologies, such as speech and optical recognition, statistical machine translation, and spelling correction. In the framework of this work, two new algorithms are introduced, for applying N-grams models in emotional speech recognition and sentence correction.