Questions tagged [natural-language-processing]

For questions related to natural language processing (NLP), which is concerned with the interactions between computers and human (or natural) languages, in particular how to create programs that process and analyze large amounts of natural language data.

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82 votes
3 answers
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How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
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  • 961
15 votes
3 answers
783 views

How would an AI learn language?

I was think about AIs and how they would work, when I realised that I couldn't think of a way that an AI could be taught language. A child tends to learn language through associations of language and ...
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  • 255
13 votes
3 answers
17k views

How do I compute the structural similarity between sentences?

I am working on a problem where I need to determine whether two sentences are similar or not. I implemented a solution using BM25 algorithm and wordnet synsets for determining syntactic & ...
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43 votes
4 answers
43k views

Why does the transformer do better than RNN and LSTM in long-range context dependencies?

I am reading the article How Transformers Work where the author writes Another problem with RNNs, and LSTMs, is that it’s hard to parallelize the work for processing sentences, since you have to ...
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  • 1,213
29 votes
9 answers
7k views

What is the actual quality of machine translations?

As an AI layman, till today I am confused by the promised and achieved improvements of automated translation. My impression is: there is still a very, very far way to go. Or are there other ...
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14 votes
3 answers
2k views

What roles knowledge bases play now and will play in the future?

Nowadays, artificial intelligence seems almost equal to machine learning, especially deep learning. Some have said that deep learning will replace human experts, traditionally very important for ...
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14 votes
1 answer
4k views

How can Transformers handle arbitrary length input?

The transformer, introduced in the paper Attention Is All You Need, is a popular new neural network architecture that is commonly viewed as an alternative to recurrent neural networks, like LSTMs and ...
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11 votes
1 answer
10k views

Are the dialogs at Sophia's (the robot) appearings scripted?

I talk about the robot from: Hanson Robotics, which was granted the right to citizenship from Saudi Arabia. I have found the following articles: Your new friend is a humanoid robot Source: ...
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  • 221
6 votes
1 answer
2k views

Did Turing foresee the required capabilities to pass the Turing test?

In Section 1.1 of Artificial Intelligence: A Modern Approach, it is stated that a computer which passes the Turing Test would need 4 capabilities, and that these 4 capabilities comprise most of the ...
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4 votes
2 answers
137 views

What is the intuition behind how word embeddings bring information to a neural network?

How is it that a word embedding layer (say word2vec) brings more insights to the neural network compared to a simple one-hot encoded layer? I understand how the word embedding carries some semantic ...
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  • 189
1 vote
1 answer
189 views

How to design a NLP algorithm to find a food item in menu card list?

I am new to NLP and AI in general. I am just expecting springboard information so that I can skip all the introduction to NLP websites. I have just started studying NLP and want to know how to go ...
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13 votes
3 answers
2k views

What are the specific requirements of the Turing test?

What are the specific requirements of the Turing test? What requirements if any must the evaluator fulfill in order to be qualified to give the test? Must there always be two participants in the ...
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  • 243
3 votes
2 answers
118 views

Why do we commonly use the $\log$ to squash frequencies?

Term frequency and inverse document frequency are well-known terms in information retrieval. I am presenting the definitions for both from p:12,13 of Vector Semantics and Embeddings On term frequency ...
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  • 2,977
3 votes
0 answers
56 views

What is the difference between zero-padding and character-padding in Recurrent Neural Networks?

For RNN's to work efficiently, we vectorize the operations, which results in an input matrix of shape (m, max_seq_len) where m ...
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3 votes
0 answers
86 views

Is there a good book or paper on word embeddings?

Is there a good and modern book that focuses on word embeddings and their applications? It would also be ok to provide the name of a paper that provides a good overview of word embeddings.
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  • 879
3 votes
1 answer
51 views

How much the dialects recognition and speech recognition are relevant?

In this tutorial, they build a speech recognition model to classify a one-second audio clip as one of ten predefined words. Suppose that we modified this problem as the following: Given an Arabic ...
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2 votes
0 answers
180 views

How do the sine and cosine functions encode position in the transformer?

After going through both the "Illustrated Transformer" and "Annotated Transformer" blog posts, I still don't understand how the sinusoidal encodings are representing the position of elements in the ...
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  • 121
1 vote
0 answers
82 views

Why is the sample size of stochastic gradient descent a power of 2?

I watched the video lecture of cs224: Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 2 – Word Vectors and Word Senses. They take the sample size of the window to be $2^5 = 32$ or $2^6 ...
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  • 1,213
0 votes
0 answers
24 views

Understanding how continuous bag of words method learns embedded representations

I'm reading notes on word vectors here. Specifically, I'm referring to section 4.2 on page 7. First, regarding points 1 to 6 - here's my understanding: If we have a vocabulary $V$, the naive way to ...
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0 votes
0 answers
17 views

Variational AutoEncoders | Is Latent space an Embedding space? [duplicate]

I am learning about Variational Autoencoders and it is mentioned that the objective of an encoder is to produce a latent space, "encoding vector". Question: Is latent space just an "...
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