Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: N-gram language models are a major resource bottleneck in machine translation. ,  present several language model implementations that are both highly compact and fast to query. Our fastest implementation is as fast as the widely used SRILM while requiring only 25% of the storage. Our most compact representation can store all 4 billion n-grams and associated counts for the Google n-gram corpus in 23 bits per n-gram, the most compact lossless representation to date, and even more compact than recent lossy compression techniques.  also discuss techniques for improving query speed during decoding, including a simple but novel language model caching technique that improves the query speed of our language models (and SRILM) by up to 300%.
['Adam Pauls', 'Daniel N. Klein']
I am writing a research paper on a idea Faster and Smaller N-Gram Language Models
[{"from": "human", "value": "I am writing a research paper on a idea Faster and Smaller N-Gram Language Models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: N-gram language models are a major resource bottleneck in machine translation. ,  present several language model implementations that are both highly compact and fast to query. Our fastest implementation is as fast as the widely used SRILM while requiring only 25% of the storage. Our most compact representation can store all 4 billion n-grams and associated counts for the Google n-gram corpus in 23 bits per n-gram, the most compact lossless representation to date, and even more compact than recent lossy compression techniques.  also discuss techniques for improving query speed during decoding, including a simple but novel language model caching technique that improves the query speed of our language models (and SRILM) by up to 300%."}]