6 votes
Accepted

What is the difference between a language model and a word embedding?

Simplified: Word Embeddings does not consider context, Language Models does. For e.g Word2Vec, GloVe, or fastText, there exists one fixed vector per word. Think of the following two sentences: The ...
Isbister's user avatar
  • 186
3 votes

What is the difference between a language model and a word embedding?

A language model aims to estimate the probability of one or more words given the surrounding words. Given a sentence composed of $w_{1},...,w_{i-1},\_ , w_{i+1},..,w_{n}$, you can find which is the i-...
SMattia's user avatar
  • 41
1 vote

What are the differences between BLEU and METEOR?

Both BLEU and METEOR are meant to evaluate the overall translation quality. METEOR shows a slightly better correlation with human judgment than BLEU, however, it relies on n-gram alignment between the ...
Jindřich's user avatar
  • 391
1 vote
Accepted

Does it make sense to use BLEU or ROUGE for any machine translation task?

Yes - and no. The important distinction is whether your data contains proper word boundaries and rigorous translation references. BLEU and ROGUE both work by comparing a candidate (ie, model output) ...
Recessive's user avatar
  • 1,396
1 vote
Accepted

What happens when the output length in the brevity penalty is zero?

Division by zero is not mathematically defined. A usual or standard way of dealing with this issue is to raise an exception. For example, in Python, the exception ...
nbro's user avatar
  • 40.5k
1 vote

Why is the perplexity a good evaluation metric for chatbots?

With perplexity you are trying to evaluate the similarity between the token (in your case probably sentences) distribution generated by the model and the one in the test data. For instance, assuming ...
ginge's user avatar
  • 146

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