HPBT is a machine translation approach that uses a phrase-based translation model and a hierarchical language model. Using probabilities, this model captures the syntactic and semantic dependencies between words in a sentence, making it the most commonly used model.
The HPBT approach has outperformed conventional phrase-based translation models on a variety of tasks, including machine translation, information retrieval, and question answering. In recent years, the basic concept of HPBT has been extended to other domains such as natural language processing and computer vision.
Pros and Cons
Advantages of SMT Versus Rules-Based Translation
Statistical machine translation has many advantages afghanistan mobile database over traditional rule-based methods of machine translation.
Saves Businesses Money
SMT is much cheaper and faster than rules-based translation or human translation. As such, it saves you money and valuable time, which is critical when competing in the tech, medical, IT, or e-commerce sectors.
Easier To Develop SMT Models
Rules-based approaches require rules for each language, and it is difficult to create large dictionaries and compile grammatical rules. So, creating statistical models for multiple languages requires less time and painstaking work than developing separate rule-based systems for each language.