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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25 views

Which Python AI library should I use when my input is a dictionary? [closed]

I want to program an AI with Python that takes a dictionary of lists as input and outputs a number or string (whichever is easier to work with). I tried googling all possibilities, but I didn't found ...
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1answer
24 views

An online editor that allows data labeling format

I have a set of students (~20) that will work on annotating data for an NLP project. The annotation task will be as in the following: ...
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11 views

Performance metric for multi aspect extraction and sentiment analysis

I created a model that extracts aspects from reviews and predicts the associated sentiments. I'm now trying to evaluate the model. I tried many different approaches because there are no real true ...
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16 views

How will actual labels be matched with predicted labels when LSTM discards data even from current time stamp input data?

I read the tutorial of LSTM from here. However, I have certain doubts that I need to address. Since we use true labels and do not remove anything from the original data, then how is it possible for ...
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26 views

Isn't attention mask for BERT model useless?

I have just dived into deep learning for NLP, and now I'm learning how the BERT model works. What I found odd is why the BERT model needs to have an attention mask. As clearly shown in this tutorial ...
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1answer
32 views

Building an AI that predicts the pronunciation of words

I want to create an AI that converts words to International Phonetic Alphabet (IPA), but I am not sure which architecture I am supposed to use. It is not possible to translate the characters one by ...
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7 views

What next after LDA and NMF for topic modelling (with Python)?

I have used NMF and LDA for topic modelling in Python, with what I would call good results with NMF, and poor results with LDA. My data is highly domain-specific, with a lot of unique/specific ...
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1answer
44 views

The model learns well, but the validation decreases over time [closed]

I have trained a model for four days. I noticed a behaviour quite strange/unnatural. During the training, the score and loss look like this: However, when I see the validation score, I got: It seems ...
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3 views

Ensure trained word embeddings get high similarity with particular words

I am trying out my hand at training a Word2Vec model using gensim. I made a simple training file that basically had just one line repeated multiple times ...
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6 views

Part of Speech and word embedding on a mobile phone1

I have a model on Spacy that does part of speech recognition and then makes a smart average of words for each part of speech: subject, verb, object... I would like to deploy it in a mobile app that ...
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1answer
11 views

Language Processing: Determine if one paragraph is relevant to another paragraph

Context: I want to determine if someone's written review contains content that is relevant to a paragraph that they are reviewing. To do so, I am trying to determine if one paragraph is relevant to ...
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10 views

Semantic-based evaluation of translations instead of BLEU

I have a text generation model and I want to evaluate its output by comparing it to a set of gold human-annotated references. I went through machine-translation metrics and I found that BLEU is used ...
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1answer
31 views

How to measure the similarity the pronunciation of two words?

I would like to know how I could measure the pronunciation of two words. These two words are quite similar and differ only in one vowel. I know there is, e.g., the Hamming distance or the Levenshtein ...
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20 views

How to Study Improving In-depth Reading Comprehension?

There are multiple datasets for machine comprehension tasks such as SQuAD. However, most of the questions are straightforward. One can find the answers easily by using the find feature of the browser ...
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1answer
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How would the probability of a document $P(d)$ be computed in the Naive Bayes classifier?

In naive Bayes classification, we estimate the class of a document as follows $$\hat{c} = \arg \max_{c \in C} P(c \mid d) = \arg \max_{c \in C} \dfrac{ P(d \mid c)P(c) }{P(d)} $$ It has been said in ...
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1answer
27 views

Are the held-out datasets used for testing, validation or both?

I came across a new term "held-out corpora" and I confused regarding its usage in the NLP domain Consider the following three paragraphs from N-gram Language Models #1: held-out corpora as a ...
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14 views

Is it possible to identify multiple queries/intents in an email, check if the reply has addressed all of those queries before sending email?

An email may contain multiple questions related to similar or distinct topics. The person responding the email needs assistance in detecting and informing if all of the questions have been addressed ...
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11 views

How does the bigram terms are contributing to sophisticated version of linear interpolation?

While studying about linear interpolation technique in natural language processing to deal with less frequent $n-$gram. I came across a sophisticated version of linear interpolation. The simple and ...
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22 views

What exactly “adjusted count” tells us in Laplace smoothing?

The probability/frequency of a word $w_i$ in an $N$-word corpus is given by $$p(w_i) = \dfrac{c_i}{N}$$ where $c_i$ is the number of times the word $w_i$ appears in the corpus. Suppose there are $V$ ...
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2answers
34 views

Example of lemma having multiple boldface forms

Number of lemmas can be used as a rough measure for the number of words in a language. A lemma can have multiple word-form types. It can be understood from the following paragraph taken from p12 of ...
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1answer
29 views

Which tasks are called as downstream tasks?

The following paragraph from p331 of the textbook Natural Language Processing by Jacob Eisenstein. It mentions about certain type of tasks called as downstream tasks. But, it provide no further ...
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16 views

Is there any dataset to convert text to sign language?

I'm going to start working on one university project and I would like to ask a question regarding it. My project is about "Sign language synthesis from NLP" and I need to develop an ...
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1answer
22 views

Extracting keywords from messages

I'm starting a project where I want to extract keywords from given messages. The keywords are for example something like: "hard disk", "watch" or other technical components. I'm ...
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1answer
45 views

How do very rare words tend to have very high PMI values?

Consider the following formulation for pointwise mutual information (PMI): $$\text{PMI}(w, c) = \dfrac{p(w, c)}{p(w)p(c)}$$ Suppose there are $W$ words with $C$ context words. Then one can write in ...
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2answers
76 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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12 views

Does the transformers model (in “Attention is All You Need”) exclude the encoder in language modelling tasks?

The language model I am referring to is the one outlined in "Attention is All You Need": My understanding is that when the task is translation, the encoder's input could be "Hi, my ...
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11 views

MBART and better Domain Specific Translations Using Masks?

I'm implementing https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt for translations as it has shown promising results but I wanted to see if there was a way to translate specific parts ...
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18 views

Understanding manual test cases

I have a large number of manual test cases which are designed to test a web application's functionality. I want to automate these and I have been exploring NLP to structurize the test cases. These ...
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1answer
20 views

Changing a CNN-LSTM image captioning architecture to use BiLSTMs

Currently I'm dealing with an assignment that made us implement the network mentioned in this paper. The network has an architecture similar to this: As you can see it uses a Unidirectional RNN (in ...
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1answer
44 views

Which AI techniques are there that combine multiple models to make sense of data at different stages?

I have been working to design a system that uses multiple machine learning models to make sense of data that is dynamically webscraped. Each AI would handle a specific task, for example: An AI model ...
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0answers
21 views

Why are BERT embeddings interpreted as representations of the corresponding words?

It's often assumed in literature that BERT embeddings are contextual representations of the corresponding word. That is, if the 5th word is "cold", then the 5th BERT embedding is a ...
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17 views

Open Domain Chatbot with intervention

As per my knowledge, there are 2 type of Chatbots- Open Domain and Closed Doman Intent Based. I was wondering how are conversational agents created such that can converse as if they are Open Domain, ...
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32 views

How do sparse word embeddings fail to capture synonymy?

While reading some explanations of why dense word embeddings work better than sparse word embeddings, the following statement has been given in the chapter Vector Semantics and Embeddings, showing a ...
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1answer
38 views

What is an “input embedding” in the context of NLP?

When reading about NLP, I saw it said that "input embeddings" are a main element of encoder-decoder learning frameworks for sequence modelling. What is an "input embedding" in the ...
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0answers
14 views

Can unsupervised models learn something from cat vocalizations?

I love cats, and over the years have noticed that they have recurrent patterns of vocalizations. For example, upon seeing a bird, a cat may start chittering, but the same cat would never chitter at ...
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1answer
34 views

How to perform multi-class text classification with a dataset of 80 documents?

I have a training dataset of 80 text documents with an average number of characters in each document of 25000 and 210 unique tags. How can I perform multi-class text classification with such a small ...
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0answers
9 views

How can I design a machine translation model that produces a mapping between the words in the source and target sentences?

I have a dataset of sentences of language X and Y X Y abc def lang xyz pqrt mno uages I want to have an output as a table with word-by-word translation (...
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1answer
51 views

Seeking advice: Building a NLP in C++ [closed]

Context: I'm taking an advanced C++ course and there is a large 2 month project of my choosing that I'll be starting soon. I want to build a NLP that can do text completion, but I'm new to this area ...
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1answer
22 views

How to build a custom morphological analyser for translation system

I want to build a machine translation system from English to Georgian. Georgian is a language similar (and simpler) to the Russian language. its syntax looks like base + suffix, only suffix changes, ...
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2answers
78 views

Book(s) for text embedding

Text here refers to either character or word or sentence. Is there any recent textbook that encompasses from classical methods to the modern techniques for embedding texts? If a single textbook is ...
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0answers
16 views

Current extensions of the “Turing Test”?

In 2014 it was widely reported that the Turing Test had been passed, and that this was a major AI milestone. See: Computer AI passes Turing test in 'world first [BBC]; Turing Test Success Marks ...
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12 views

ML model to predict values from text (a lot of training training data)

I have around 1M entries of the type: id | big5_openness | big5_conscientiousness | big5_extraversion | big5_agreeableness | big5_neuroticism | input_text Where <...
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0answers
10 views

How to detect the description of spine segments in short text using a neural network?

The input data is a set of text chunks containing the description of the pathology or the surgical procedure: For instance: Tere is a lumbar stenosis L3/4 Patient ist suffering from [...], MRI and X ...
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12 views

How to Approach a Conversation Detector?

I am currently looking for a way to detect if a conversation is occurring. The meaning of the conversation is not important for this case. One approach that seems viable is to try to detect a voice ...
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11 views

Does it make sense to generate sentences with Transformer's encoder?

Quite a few vision+language papers pretrain BERT-based model with image-text data and finetune for image captioning task. But there is no decoder involved to generate sentences. Does that make sense? ...
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27 views

Do the training and test datasets need to be equally preprocessed as one whole dataset?

I have developed, trained and tested an NLP model. It is persisted in a pickle file. The model contains the data preprocessing function that includes text cleaning and new features engineered with ...
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1answer
2k views

What language is the GPT-3 engine written in?

I know that the API is python based, but what's the gpt-3 engine written in mostly? C? C++? I'm having some trouble finding this info.
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21 views

Speech diarization for a conversation detector: A good idea or not?

I am trying to write a program in which an ai can detect whether a conversation is occurring or not. The ai does not need to transcribe words or have any meaning about the conversation, simply if one ...
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0answers
15 views

Can I use the phi coefficient to compare predictions by two different classifiers?

Can I use the Matthews correlation coefficient (aka phi coefficient) to compare predictions by two different classifiers? That is, is this code correct if I want to check how diverse/correlated my two ...
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33 views

Why does KNN algorithm perform better on Word2Vec than on TF-IDF vector representation?

I am doing a project on multi-class text classification and could do with some advice. I have a dataset of reviews that are classified into 7 product categories. Firstly, I create a term-document ...

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