Language Modeling is a fundamental concept in Natural Language Processing (NLP). It involves creating a model that can predict the next word or sequence of words in a given text. This technology is used in various applications, such as machine translation, text generation, and speech recognition.
Key Components of Language Modeling
- Probability Distribution: A language model assigns probabilities to sequences of words.
- N-gram Models: These models predict the next word based on the previous N words.
- Neural Networks: Deep learning models like Recurrent Neural Networks (RNNs) and Transformer models are widely used for language modeling.
Applications of Language Modeling
- Machine Translation: Language models help in translating text from one language to another.
- Text Generation: They can be used to generate new text, such as poems, stories, or articles.
- Speech Recognition: Language models assist in converting spoken language into written text.
Language Modeling in NLP
For more information on language modeling, you can explore our comprehensive guide on Natural Language Processing.