Questions tagged [natural-language-processing]

For questions related to natural language processing, which 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.

Filter by
Sorted by
Tagged with
0
votes
0answers
18 views

How can I do entity recognition given the features?

I constructed the features from this tutorial: https://sklearn-crfsuite.readthedocs.io/en/latest/tutorial.html#features. But I did not understand the process of making the model. After doing the ...
3
votes
0answers
21 views

Can computers recognise “grouping” from voice tonality?

In human communication, tonality or tonal language play many complex information, including emotions and motives. But excluding such complex aspects, tonality serves some a very basic purpose of "...
2
votes
0answers
46 views

What is a conditional random field?

I new in machine learning, especially in Conditional Random Fields (CRF). I have read several articles and papers and in there is always associated with HMM and sequences classification. I don't ...
1
vote
0answers
17 views

Models to extract Causal Relationship between entities in a document using Natural Language Processing techniques

I am looking to extract causal relations between entities like Drug and Adverse Effect in a document. Are there any proven NLP or AI techniques to handle the same. Also are there ways to handle cases ...
0
votes
1answer
38 views

How do I classify strings with possibly no meaning?

I am quite new to text classification. Using EAST text detection model, I get multiple strings that aren't words and most often have no meaning. For example, IDs, brand names, etc. I would like to ...
0
votes
1answer
24 views

Is there any way to classify Document Image without OCR?

I have multiple invoices images which need to classify invoice types such as fright, utility, goods, etc. Is there any way to classify without OCR?
2
votes
1answer
55 views

Adding BERT embeddings in LSTM embedding Layer

I am planning to use BERT embeddings in the LSTM embedding layer instead of the usual Word2vec/Glove Embeddings. What are the possible ways to do that?
3
votes
1answer
69 views

How can I build an AI with NLP that read stories

I want to do an NLP project but I don't know if it's doable or not as I have no experience or knowledge in NLP or ML yet. The idea is as follows: Let's say we have a story (in the text) that has 10 ...
1
vote
1answer
39 views

Do I need to use a pre-processed dataset to classify comments?

I want to use Machine Learning for text classification, more precisely, I want to determine whether a text (or comment) is positive or negative. I can download a dataset with 120 million comments. I ...
1
vote
0answers
22 views

Conversational AI

I'm wondering if anyone knows about any projects that break down conversations for an AI. I'll explain what I mean - I've seen a lot of hardcoded responses, but nothing that allows an AI to break a ...
0
votes
0answers
21 views

How Seq2Seq with Bidirectional RNN works?

First of all the scope of the question is as follows - we have Sequence2Sequence architecture with: Decoder: Bidirectional LSTM Encoder: regular (single directional) LSTM What I know: When you ...
1
vote
1answer
34 views

How to distinguish between proper nouns and other words in NLP?

If an NLP system processes a text containing proper nouns like names, trade marks, etc. without knowing anything about the language (ie no lexicon), is it possible to recognise them?
26
votes
9answers
6k views

What is the actual quality of machine translations?

Till today I - as an AI layman - 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 ...
3
votes
1answer
39 views

Will BERT embedding be always same for a given document when used as a feature extractor

When we use BERT embeddings for a classification task, would we get different embeddings everytime we pass the same text through the BERT architecture? If yes, is it the right way to use the ...
1
vote
0answers
24 views

Generate QA dataset from large text corpus

I have a corpus of a domain data in form of 10-15 books pdf and some articles and my end-goal is to make a question-answering system particular to that domain. For that, I would need a dataset on Q/A ...
3
votes
1answer
51 views

How do I identify a monologue or dialogue in a conversation?

How do I identify monologues and dialogues in a conversation (or transcript) using natural language processing? How do I distinguish between the two?
1
vote
0answers
35 views

Does the human brain use beam search for text generation?

As far as I understand, beam search is the most widely used algorithm for text generation in NLP. So I was wondering: does the human brain also use beam search for text generation? If not, then what?
0
votes
2answers
64 views

How can I implement a GAN network for text (review) generation?

How can I implement a GAN network for text (review) generation? Please, can someone guide me to resource (code) to help in text generation?
1
vote
1answer
78 views

Why can we approximate the joint probability distribution using the output vector of an LSTM?

In the paper, Contextual String Embeddings for Sequence Labeling, the authors state that \begin{equation} P(x_{0:T}) = \prod_{t=0}^T P(x_t|x_{0:t-1}) \end{equation} They also state that, in the LSTM ...
1
vote
0answers
25 views

Bert super easy implementation

I myself am not new to NLP, but for some reason I am unable to grasp purity of BERT. I have seen a ton of blogs, github repos, but none could clarify BERT usage to me. It would be helpful if you ...
1
vote
1answer
14 views

Convolutional Sequence to Sequence Learning kernel parameters

I am reading the paper Convolutional Sequence to Sequence Learning by Facebook AI researchers and having trouble to understand how the dimensions of convolutional filters work here. Please take a look ...
1
vote
1answer
25 views

What data formats/pipelining are best to store and wrangle data which contains both text and float vectors?

Often in NLP project the data points contain both text and float embeddings, and it's very tricky to deal with. CSVs take up a ton of memory and are slow to load. But most the other data formats seem ...
1
vote
1answer
23 views

Having trouble figuring out how loss was calculated for SQuAD task in BERT paper

The BERT Paper https://arxiv.org/pdf/1810.04805.pdf Section 4.2 covers the SQuAD training. So from my understanding, there are two extra parameters trained, they are two vectors with the same ...
0
votes
0answers
6 views

What services are available for interpreting batches of text in order to determine their topic and/or summary?

I'm aware of the services from Microsoft and AWS, that may be able to used for such an application. Please let me know how these fare, and if other similar services exist elsewhere: https://azure....
2
votes
2answers
52 views

Do we have cross-language vector space for word embedding?

Do we have cross-language vector space for word embedding? When measure similarity for apple/Pomme/mela/Lacus/苹果/りんご, they should be the same If would be great if there's available internet service ...
1
vote
1answer
46 views

How can we create a vector space where word spelling and pronunciation can be easily compared?

In natural language processing, we can convert words to vectors (or word embeddings). In this vector space, we can measure the similarity between these word embeddings. How can we create a vector ...
0
votes
0answers
25 views

How do I create syntactically correct sentences given several words?

Is there an AI application that can produce syntactically (and semantically) correct sentences given a bag of words? For example, suppose I am given the words "cat", "fish", and "lake", then one ...
1
vote
1answer
33 views

Can AI help summarize article or abstract sentence keyword?

I'm wondering if AI now can help us abstract summary or general idea of long article, for example novel or historical stories, or abstract most important keyword from sentence; Would you please tell ...
1
vote
0answers
45 views

ChatBot applications [Academia]

I am in education and I'm wondering about the use of chatbot-like tools to facilitate automated discussions among students. The chatbot domain of knowledge would be purposely restricted to a specific ...
1
vote
0answers
53 views

How does bidirectional encoding allow the predicted word to indirectly “see itself”?

Before the release of BERT we used to say that it is not possible to train bidirectional models by simply conditioning each word on its previous and next words, since this would allow the word that’s ...
0
votes
0answers
23 views

Semantic search engine for a set of documents in python

I want to create a semantic search for a set documents with terms that could not appear on the set. Is there some code for that? I'm working on python.
1
vote
1answer
34 views

How to make meaningful sentences from a set of words?

I have set of topics generated using LDA and like {code, language, test , write, function}, {class, public, method, string, int} etc and I want to make meaningful sentence/sentences from these words ...
1
vote
2answers
60 views

Which algorithm should I use to map an input sentence to an output sentence?

I am new to NLP realm. If you have an input text "The price of orange has increased" and output text "Increase the production of orange". Can we make our RNN model to predict the output text? Or what ...
1
vote
0answers
25 views

Generate text from single word/topic using pre-trained language models such as GPT or BERT?

I have a dataset of 100000 documents each labelled with a topic to it. I want to create a model such that given a topic, the model can generate a document from it. I came across language models GPT, ...
4
votes
1answer
33 views

Cold start collaborative filtering with NLP

I’m looking to match two pieces of text - e.g. IMDb movie descriptions and each person’s description of the type of movies they like. I have an existing set of ~5000 matches between the two. I ...
2
votes
0answers
18 views

Multi-field text input for LSTM

I'm using LSTM to categorize medium-sized pieces of text. Each item to be categorized has several free-form text fields, in addition to several categorical fields. What is the best approach to using ...
0
votes
0answers
6 views

Why does fasttext have out-of-vocabulary and computational complexity problems while wordpiece does not?

For https://github.com/google-research/bert/issues/355 , why does fasttext have out-of-vocabulary and computational complexity problems while wordpiece does not ?
1
vote
0answers
24 views

Why do we need agents in Knowledge Query and Manipulation Language?

A multi-agent system is composed of multiple interacting intelligent agents on which KQML (Knowledge Query and Manipulation Language) is implemented. But I am confused on the nature of agents and why ...
3
votes
0answers
19 views

Why does all of NLP literature use noise contrastive estimation loss for negative sampling instead of sampled softmax loss?

A sampled softmax function is like a regular softmax but randomly selects a given number of 'negative' samples. This is difference than NCE Loss, which doesn't use a softmax at all, it uses a ...
0
votes
2answers
121 views

Use BERT to answer a FAQ with semantic similarity

I have been looking for BERT for many tasks and I would like to compare performance to answer a FAQ using BERT semantic similarity and BERT Q/A. However, I'm not sure it is a good idea to use ...
0
votes
2answers
62 views

how can i make meaningful english sentences from given set of words in python?

I have a set of topics and each topic consist of set of words. I want to make meaningful english sentences from these words. Each topic is consist of five to ten words and these words are relevant to ...
0
votes
1answer
24 views

Algorithms and strategies to help judges rule cases

I'm a Rails developer with a lot of web experience, but none (still) in AI. I'm working in a web text editor that judges use to writing their sentences. The goal is to start to use AI to help the ...
1
vote
1answer
46 views

Skip-Gram Model Training

Suppose we want to predict context words $w_{i-h}, \dots, w_{i+h}$ given a target word $w_i$ for a window size $h$ around the target word $w_i$. We can represent this as: $$p(w_{i-h}, \dots, w_{i+h}|...
0
votes
0answers
32 views

Facebook's Dr QA with multiple choice questions?

Is there such a thing as Facebook's Dr QA with multiple choice questions? Where the algorithm selects the most likely from 3 possible responses? The idea is to solve the following problem ...
0
votes
0answers
18 views

What are the reference papers of image captioning model 'all_img', 'att2in2', 'adaattmo' and 'topdown'?

I Want to cite the reference paper of The models appeared in this webpage: https://github.com/ruotianluo/ImageCaptioning.pytorch/blob/master/models/init.py But which papers do these four models '...
1
vote
0answers
12 views

any workaround to manipulate/transform recurrent CNN for sentence classification?

I learned how to build recurrent cnn model for text classification and sketched out my initial implementation. However, I am wondering how to transform recurrent <...
1
vote
1answer
88 views

Is Reinforcement Learning the future of Natural Language Processing?

I was reading about the grounding problem after seeing it mentioned in another answer today. The article states that, in order to avoid the "infinite regress" of defining all words with other words, ...
2
votes
1answer
76 views

How do I use neural networks to implement a chatbot?

I don't know anything about neural networks, but I got the information that making a chatbot with a neural network is very good. Is this really true? What do I need to know in order to build a chat ...
2
votes
1answer
58 views

Which matrix represents the similarity between words when using SVD?

Two words can be similar if they co-occur "a lot" together. They can also be similar if they have similar vectors. This similarity can be captured using cosine similarity. Let $A$ be a $n \times n$ ...
0
votes
0answers
21 views

Detecting an entity (location) in a text, using a corpus of smaller texts

I have a corpus of around 2000 texts, that are relatively short (+- 150 words). All of these texts are news articles about accidents that happened in the Netherlands. I'd like to extract the exact ...