[SRILM User List] how are the probabilities computed in ngram-count

[Andreas Stolcke]

On 4/11/2012 5:48 AM, Saman Noorzadeh wrote:
> Thank you,
> -cdiscount 0 works perfectly, but now that I have read about smoothing 
> and different methods of discounting I have another question:
>
> I want to know your ideas about this problem:
> I want to have a model out of a text. and then predict what the user 
> is typing (a word prediction approach). at any moment I will predict 
> what the next character would be according to my bigrams.
> Do you think methods of discounting and smoothing are useful in 
> treating the training data?
> or it is more appropriate if I just disable it?

It probably won't make a difference because in an application like this 
you are interested in finding the most probable next tokens, and 
smoothing helps you with the least probable tokens.  However, this type 
of LM application has been studied extensively, and you should look 
online what others have done.  Try

http://scholar.google.com/scholar?q=character+prediction+typing&hl=en&btnG=Search&as_sdt=1%2C5&as_sdtp=on

Andreas

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