Questions tagged [natural-language-processing]

Natural language processing (NLP)

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Query about an equation in GAN-NMT paper

So i was studing the paper Adversarial Neural Machine Translation by Lijun Wu1, Yingce Xia2, Li Zhao3, Fei Tian3, Tao Qin3, Jianhuang Lai1,4 and Tie-Yan Liu. The link to the paper is : https://arxiv....
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12 views

Understanding Multi-headed attention

Recently I came across the concepts like Attention and Transformer architecture. After studying the papers and many blogs, I understood the concepts, but recently one doubt is coming in my mind and ...
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1answer
27 views

CYK result de-transformation

Suppose we have a rules derived from a treebank. And in order to get a syntax tree of a given sentence we use the cyk algorithm. In order to use the cyk we should convert the rules into chomsky normal ...
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21 views

CYK algorithm - how to handle unknown terminals given in a sentence to parse?

There is a given treebank which we derive the Probabilistic context free grammar. I wonder how do one handles with a given sentence which includes terminals that don't exist in the derived rules? Is ...
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101 views

How does Google's Superpod work?

I was looking for the best natural language quenstion answering system and chatbots when I found Google's Superpod described here. I googled for how Superpod works but I have found any important ...
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1answer
60 views

N-gram language model question

I have this question I found regarding n-gram modelling in the Speech and language processing text book: ...
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23 views

How can I find the perplexity of a text by the perplexity of its sentences?

For a bigram language model, I can calculate the perplexity of sentences of a test document. However, I'm not sure what would be the perplexity of the whole document. Should I get the average of the ...
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1answer
134 views

Bottom up chart parser adding active arc step

I am following Bottom up chart parsing algorithm from Natural Language Understanding book by James Allen. It is I couldn't understand the 3rd step. I thought that when active arc is added the dot ...
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37 views

Text Segmentation Problem give Word Frequencies in a Universe

Given a dictionary of words and their frequencies (how many times they appear in a universe and given a string(no spaces, punctuation, etc.). What is the best way to segment into individual words? I ...
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26 views

Find pattern in string of unkown language

Hello I am looking for an algorithm which solves following problem for me. Given a text/string = 'BIRDBIRDBIRDBIRDDEVILDEVILDEVILDEVILEASYEASYEASY ...' of an unkown language. For the sake of ...
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Are there any neural NLG systems which don't generate in left-to-right order?

For a while, all classification tasks in natural language processing were based on simple RNN's, which operate in a very word-by-word order. Adding gating mechanisms increased ability to "look back", ...
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22 views

Generalization of formal grammars - production rules with more general functions?

Usually formal grammars have production rules in the format N=tNt where simple concatenation function is used for the expansion of the nonterminal. https://www....
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50 views

How to prove that katz backing off smoothing technique is a valid probability distribution?

How to prove that katz backing off smoothing technique is a valid probability distribution? Take the example of bigram. You can go through this link for katz back off model https://en.wikipedia.org/...
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66 views

Show that the Laplace smoothing for bigrams is a valid probability distribution

If we consider any smoothing technique like laplace or delta smoothing. Intuitively we can see that the we are stealing from sequences with non zero probablity and re distribute to sequences with zero ...
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1answer
96 views

How to represent symbolic knowledge using real numbers - theory about neural networks and natural/analog computing?

One can define the semantics of one definite word using the references to real world entities, relationships with the other words and other concepts and represent all this knowledge about this one ...
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70 views

FastText how it works?

So my question is how Supervised FastText works for the most part. I understood in the original paper they use bag of n-grams for features, but then they released a paper with enriching the word ...
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How to represent sentences with their dependency parses as input to an RNN?

I am working on a task embedding sentences into a lower-dimensional space according to style, both grammatical and lexical. As such, I want to have as input the linear ordering of tokens in each ...
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19 views

How to solve question answer questions using trees and graph theory?

Good evening! I'm doing an internship at Ecole Normale Supérieure of France, where they create their scholars, and I encountered a dataset I wanted to solve using graphs... I. The challenge ? ...
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How to compute the loss and backprop of word2vec skip-gram using hierarchical softmax?

So we are calculating the loss $$J(\theta) = -\frac{1}{T}\sum_{t=1}^T\sum_{-m \leq j \leq m} \log P(w_{t+j}|w_t;\theta)$$ and to do this we need to calculate $$P(o|c) = \frac{\exp(u_o^Tv_c)}{\sum \...
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1answer
91 views

How to transform lambda function to multi-argument lambda function and how to rewrite or approximate terms?

I am trying to do the formal semantics (Montague grammar, abstract categorial grammar) of natural language and encode the sentence John is boss. The type system has ...
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1answer
163 views

How does SpaCy make its dependency tree?

I discovered that SpaCy had the ability to make dependency trees. For instance given a question “To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?” We can create its dependency ...
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179 views

How can node2vec help find similar “roles” within a graph (nodes whose connections have similar structure within the graph)?

I have a question on the node2vec algorithm described in this paper. Node2vec is a deep learning algorithm that word2vec to graphs to learn embeddings. The authors claim that it can help find nodes ...
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1answer
22 views

Marginalise edge weights on graph

I have a directed acyclic graph with a score on each edge. The score of a path is defined to be the sum of the scores on the edges along this path. The probability of a path is the score of such a ...
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1answer
627 views

Subsampling of Frequent Words in Word2Vec

I am reading through the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf Under section 2.3 on page 4 the authors ...
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1answer
56 views

Question on word probability for hierarchical softmax used in natural language processing

I am reading the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf On page 4 of the paper they describe the ...
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1answer
31 views

Naive Bayes' Classification and Using the Entire Vocabulary in the Denominator

I am working through the NLP notes for Naive Bayes' classification here: https://web.stanford.edu/~jurafsky/slp3/6.pdf Below $c$ is the class of the observation and $w_i$ is the $i$th word of a text ...
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How does the Earley parser accept the input string as syntactically correct?

https://en.wikipedia.org/wiki/Earley_parser An input string of length $n$ is syntactically correct if at least one $(S \rightarrow X_1 ... X_m • 0)$ is in $E_n$. Why is this the case ? The part ...
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45 views

Proving the probability of zero occurrences in training using Good-Turing maximum likelihood estimate

Background Good-Turing (GT) smoothing is used in language models to estimate the counts of words in the test set that have not been seen in the training set. In GT smoothing, $N_c$ is the count of ...
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27 views

Any references/current work on anomaly detection in conversations?

Suppose I have a lot of data on conversations between humans and chatbots (human text, chatbot text, times, media used for chat, etc), and I want to be able to detect anomalies in these conversations. ...
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51 views

Automatic learning/discovery of logics

Are there efforts to automatically discover new logics? Logics are simple structures - they have formal language, deduction rules, semantics and certain properties that are proved or discarded for ...
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114 views

Semantic parsing with Grammatical Framework - is this possible?

So far I have learned about categorial grammars, type logical grammars and formal semantics of natural language, the relevant tools are Cornell Semantic Parsing Framework https://github.com/clic-lab/...
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1answer
30 views

How to figure out whether two texts refer to the same object or event

Let's assume there is something happen in the world - Football world cup final. And team-1 beat team-2 with the score 3:2. So there is whole bunch of articles on every website about it, each contains ...
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1answer
149 views

Converting CFG to CNF [closed]

need some help with the following question: I've watched a few youtube tutorials but I'm struggling to convert this specific CFG
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86 views

How to translate lambda calculus into (first-order, modal) logic, is it possible at all?

It is possible (using formal semantics) to translate natural language sentences into lambda expressions. So, is it possible to translate those lambda expressions into some logic, e.g. into first-order ...
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47 views

Semantic/DRT methods for conversational agents / chatbots / dialogue systems - reference request?

The wiki pages about chabots mention that statistical methods, keyword search and precompiled answers are used for the chatbots. But I feel that there should exist different - semantical approach for ...
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1answer
523 views

nlp: phonetic edit distance between a word and the closest of a set of words

Let's say someone is using Dragon Dictation, Google Speech, or some other free form dictation software (it will recognize anything they say to the best of its ability). I have some reasonably large ...
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1answer
50 views

Understanding the geometrical interpretation of word2vec

I'm trying to understand how the $word2vec$ method actually nudges word vectors of similar semantic/syntactic content closer together in the word vector space. I've read here (Quora answer) that it's ...
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76 views

HMM Baum-Welch training and pruning

I am working on a HMM tagger that should be initialized with some small data and then supposedly improved with Baum-Welch algorithm on the data. However, the number of states is huge, almost $459^2$, ...
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1answer
27 views

HMM tagger - Baum Welch training

I am trying to implement a trigram HMM tagger for a language that has over 1000 tags. In my training data I have 459 tags. Now if we consider that states of the HMM are all possible bigrams of tags, ...
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1answer
23 views

How to use a logistic regression classifier to estimate the confidence of a rule?

The following is an excerpt from the Estimating LAT Confidence section of this paper: ... Since some LAT detection rules are more reliable than others, we would like to have a confidence value in ...
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1answer
28 views

Using Graphs to construct semi-supervised learning solution

I am currently trying to design a graph-based approach for content tagging. In principle I am trying to two two things: Use an algorithm such as Latent Dirichlet Allocation (LDA) or some variant of ...
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383 views

How much training data for speech recognition?

How much training data is needed to build a speech-to-text engine based on machine learning? (To within an order of magnitude or so.) Big companies like Google, Facebook have a massive amount of data....
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1answer
86 views

How to express modalities in lambda calculus - are some extensions required?

Lambda calculus can be used for encoding semantics of natural language, e.g. http://yoavartzi.com/tutorial/ contains full details about semantic parsing of natural language: converting natural ...
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1answer
239 views

Semantic readings of the Lambek sequent calculus

I am reading Categorial Grammar: Logical Syntax, Semantics, and Processing by Glyn Morrill and I am stuck with the Fig. 3.9: Can someone explain this set of formulas and |.| function specifically? ...
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47 views

Training algorithm for Manual error correction in text

I want to work on a model where I make some manual corrections in my clinical notes data and want the neural network to learn those corrections.The algorithm will be supplied with both corrected and ...
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76 views

Which Machine Learning algorithm should I use for gender tagging of words in NLP? [closed]

I have a dataset of about 26,000 words along with their gender tags [m, f or any]. Which ML algorithm should I use for Gender Tagging/Classification purpose. How should I go about it? What should be ...
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36 views

Outline detection from patterns in a list of textual articles

Are there NLP algorithms dealing with detecting the repeating patterns in a a list of texts from which a topic keywords and other associative keywords can be derived? I will show it as an example: ...
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1answer
221 views

TF IDF Spark values are small after cosine similarity

I am creating a software that computes the cosine similarity between 2 strings. I am using Spark as I have to use Java. I created a Bag of words model and computed the cosine similarity successfully. ...
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2answers
578 views

Examples for CFG that cannot be expressed by regular language

There are nice examples for context free grammars which cannot be expressed with regular language, for example the palindrome and a similar contrived example here, but they are very intuitively ...
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45 views

Speech to Text API with Unknown Language

I would like to develop an application that outputs text from the audio of 2 possible languages. For ex: Audio might be English or Spanish, it should return the spoken words. Most speech to text ...