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Questions tagged [natural-language-process]

Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input, and others involve natural language generation. See NLP.

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12 views

Usage of GPT2-Double-Heads-Model

According to the HuggingFace Transformer's website (https://huggingface.co/transformers/model_doc/gpt2.html#gpt2doubleheadsmodel), GPT2DoubleHeadsModel (NOT GPT2LMHeadModel but GPT2DoubleHeadsModel) ...
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Generate Intro-Text for Newsletter

I am trying to implement the following idea. For a daily newsletter I would like to generate an engaging and funny intro text, such as: Good morning. Sorry if there are beer stains and buffalo ...
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Unable to understand the following part of the research paper [on hold]

I am currently reading the following research paper https://www.researchgate.net/publication/326013025_New_doctors_ranking_system_based_on_VIKOR_method And I am unable to understand the Process: 3.1....
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what is the difference between these NLP terms latent,syntatic, semantic and context of words in sentence? [on hold]

what are these terms used in natural language processing used for : latent,syntactic, semantic and context? they all look similar to me .
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what is BIO Tags for creating custom NER Named entity recognization?

I want to create custom NER Named entity recognition but im confused with this part of what is BIO Tags .Can any please explain the steps for creating NER anda bout this B,I,O tag .
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123 views

Which neural network to choose for classification from text/speech?

I am considering two tasks: Dialog Act Classification from Text (e.g. classify to: question; opinion; ...) Emotion Recognition from Speech (e.g. happy; calm; sad; ...) Which DL model should perform ...
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7 views

Building a diagnostic chatbot [on hold]

Please help me improve my question if you think it's not good in some way. I am new to both StackExchange and data science. I am building a chatbot for running diagnostics on some complex mechanical ...
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12 views

BERT Model Evaluation Measure in terms of Syntax Correctness and Semantic Coherence

For example I have an original sentence. The word barking corresponds to the word that is missing. ...
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1answer
16 views

Looking for a causality to effect dataset

I am looking for a causality dataset that would look like this: ...
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Absolute Discounting: How are we guaranteed that the n-gram count in training set will differ from the count in held-out corpus by a fixed number

In "August 2019 draft of the 3rd edition of Jurafsky & Martin Speech and Language Processing" book's section 3.5 (Kneser-Ney Smoothing) it is stated that The astute reader may have noticed that ...
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What is the use of [SEP] in paper BERT?

I know that [CLS] means the start of a sentence and [SEP] makes BERT know the second sentence has begun. However, I have a question. If I have 2 sentences, which are s1 and s2, and our fine-tuning ...
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25 views

Is there any text similarity databse available for phrases?

I want to train my application for phrase similarity. I want my model to predict similarity score for phrases as shown in below examples. ex- ...
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1answer
23 views

How to group chat messages by topic?

I am a newbie in this field. Developer since 20 years and more but never done anything (except tutorials) with ML, DL, and NLP. Though I've already read a bunch of articles and tutorials about this ...
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NL2SQL task, if we have enough data, what will the model achieve for hard SQL?

We are afraid that the hard SQL like TABLE JOIN is the limit for industrial application. Addition info: https://yale-lily.github.io/spider Thank you very much.
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How to generate alignments for word-based translation models if number of words are different in both sentences

I am working on implementing IBM Model 1. I have a parallel corpus of some 20,00,000 sentences (English to Dutch). Also, the sentences of the two docs are already aligned. Aim is to translate a Dutch ...
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100 views

Framing Sentences based on keywords

Given a few specific words, which techniques of Natural Language Processing can I use to achieve creating a meaningful sentence from those words? eg. Words: jackets, highest sale, sweaters, lowest ...
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Why don't we use BCE(Binary Cross Entropy) for language modeling?

I've seen a lot of RNN/Transformer models use cross entropy loss with softmax. but isn't language modeling a multilabel classification task? what happens if we replace cross entropy loss with binary ...
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How do I visualize data for a natural language processing project?

I am using a question-and-answer dataset. My neural network takes a question and an article content, and outputs where an answer starts (as an integer). To visualize my data, how should I process it ...
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1answer
14 views

Automatically categorize parts of a piece of writing

Suppose I had a piece of writing. The document contains aspects like questions, assertions, examples, and explanations. Is it possible to use Natural Language Processing to categorize each sentence of ...
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1answer
279 views

Trying to implement a “smart compose” feature

I found this post on Gmail's smart compose feature, and it got me thinking about trying to implement it myself. https://ai.googleblog.com/2018/05/smart-compose-using-neural-networks-to.html The text ...
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Combining two structurally similar datasets from different sources

I am working with a text summarization problem, and I am trying to use this architecture [Pointer Generator]. My data set is VERY small (225 samples) compared to the CNN/ Daily Mail dataset this paper ...
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What's the size of Google's complete Conceptual Captions image captioning dataset with all the images downloaded from the listed URLs?

The original dataset provided by Google, here, consists of 'Image URL - Caption' pairs in both the provided training and validation sets. I have to work on an image captioning project and wanted to ...
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126 views

Why is word prediction an obsession in Natural Language Processing?

I have heard how great BERT is at masked word prediction, i.e. predicting a missing word from a sentence. In a Medium post about BERT, it says: The basic task of a language model is to predict ...
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How prevalent is `C/C++` in machine learning development?

I am currently a data scientist mostly doing NLP, and I do most of my work inPython. Since I didn't get a CS degree in undergrad, I've been limited to very high ...
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Finding Criminal Name in news?

We have news URLS, which we want to classify into crimes or non-crimes and further identify criminals by using NERs. For creating a model that identifies criminals, we tried SPacy which gave all the ...
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can we learn a model to pre-process text? [closed]

I'm in a very dire situation where I have to preprocess the text but the text in the documents is very random. It is in the form of numerical points. I want to remove a certain class of points (...
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What's the best way to store BERT training data (input IDs)

The tricky thing about the input IDs is what they're varying in length for each data sample, so regular hdf5 may not be ideal. Since Bert is so popular I am wondering if there's an established way to ...
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1answer
21 views

What is the easiest way to identify a gender for a noun (in a french)?

I am working on an app where in order to process some data, I need to be able to identify the gender for some selected words. My data is in French. The feature I am looking for should be able to tell ...
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1answer
35 views

What does the dimension represent in the GloVe pre-trained word vectors?

I'm using GloVe pre-trained word vectors (glove.6b.50d.txt, glove.6b.300d.txt) to word embedding. I have a conceptual question: What is the difference between these files? On the other hand, what ...
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52 views

How to cluster n-grams?

I just wanted to know how to cluster n-grams based on their semantics. Like clustering together n-grams that are semantically similar by leveraging the distributional hypothesis suggesting that ...
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16k views

Natural Language to SQL query

I have been working on developing a system "Converting Natural Language to SQL Query". I have read the answers from the similar questions, but was not able to get the information that I was looking ...
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1answer
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Identifying if the sentence if it comprise information about education

Given a sentence I am trying to classify if the sentence contain information about education. For example: ...
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Combining decision trees and neural networks for classifying text with metadata . How to combine and train?

I have a multi-label classification problem where the input consist of free text, with metadata such as categories (from a fixed, limited set) associated with each text. The output consist of a set of ...
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19 views

Simplest way to build a semantic analyzer

I want to build a semantic analyzer i.e., to find how similar the meaning of two sentences are. For example- English: Birdie is washing itself in the water basin. English Paraphrase: The bird is ...
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1answer
61 views

How to extract location related terms from raw text in python

I want to extract location related keywords from raw text in python. I have already tried spacy but the results were not good and I just got names of countries while I want fine-grained location ...
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2answers
132 views

How do you measure performance for word prediction tasks?

Say I have to predict the next word in a sentence, given the initial few words. Suppose the prefix is "I went to _____". This prefix is common enough that it might appear 10 times in the training ...
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Assign Topic to a document after LDA

I executed my LDA and now I have several topics with their word distributions. How do I assign each document to a topic? Is Euclidean distance a good choice? Or there are other methods? Thanks
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1answer
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Document embedding vs locality sensitive hashing for document clustering

I would like to compare two methods: locality sensitivity hashing and document embedding to get the similarity between two documents. Both of those methods encode information of a document in a ...
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POS extraction using CoreNLP

I have a corpus of windows related documents, for which I need to extract nouns and verbs. However, it is required that I keep certain windows specific words such as "inline hooking", "instruction ...
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1answer
22 views

Using Keras how and what do I need to export to use my classifier independently?

I have a basic question that I can't seem to find an answer to. I built and trained with good results (above 90% accuracy) a NLP Log classifier that takes in a UTF-8 payload and classifies it into 32 ...
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3answers
73 views

Using Google Translate API to create a Translation Dataset

Is it a good idea? ;-) Is it legal to do so? Is it legal to release such a dataset to public? Say I have a language X for which I want to create a dataset for translation to/from English, for which I ...
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How to extract electroglottograph/laryngograph using python(specially in “librosa”)?

in a certain project of mine which is related to feature extraction from speech data, I want to extract some electroglottograph/laryngograph from speech data, I have read some research papers but ...
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86 views

*Challenge* Making an algo that learns from a book, and can answer anything about it

I recently took this challenge where I am trying to make a set of algorithms to read any particular book, understand and store the context and subsequently answer any question asked about it. In ways ...
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Where can I get an untokenized version of GLUE's SST-2 dataset?

On the GLUE faq, they say: Similarly, for SST, the data provided is already tokenized. We're working on obtaining a version that is not tokenized. Feel free to train on other distributions of ...
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1answer
22 views

Is it possible to create a rule-based algorithm to compute the relevance score of question-answer pair?

In information retrieval or question answering system, we use TD-IDF or BM25 to compute the similarity score of question-question pair as the baseline or coarse ranking for deep learning. In ...
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44 views

What is the State-of-the-Art open source Voice Cloning tool right now?

I would like to clone a voice as precisely as possible. Lately, impressive models have been released that only need about 10 s of voice input (cf. https://github.com/CorentinJ/Real-Time-Voice-Cloning),...
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48 views

NMT, What if we do not pass input for decoder?

For transformer-based neural machine translation (NMT), take English-Chinese for example, we pass English for encoder and use decoder input(Chinese) attend to encoder output, then final output. What ...
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What can NLI do for a chatbot?

Natural Language Inference(NLI) is the task of predicting the labels(entailment, contradiction, and neutral,) for sentence pairs. People invent a lot of deep model to solve this problem. But I can ...
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Step extraction from a paragraph

Came across an interesting problem: Given a paragraph describing how to do a process, need to break it down to various steps. Basically, need to determine for each sentence in the paragraph, if this ...
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1answer
31 views

Guidelines to debug REINFORCE-type algorithms?

I implemented a self-critical policy gradient (as described here), for text summarization. However, after training, the results are not as high as expected (actually lower than without RL...). I'm ...