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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How to implement LSTM using Doc2Vec vectors to get representation?

Hi all. I'm a newbie in ML. I read and found a paper about A Multi-Level Plagiarism Detection System Based on Deep Learning Algorithms and want to implement this model . But I can't find more about ...
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What should return doc.ents if the doc have no entities, in spacy?

I want to answer this question: "How many sentences contain named entities given a doc?" and I have this piece of code as solution ...
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can someone give me an idea how to extract information for text such as invoice bills using natural language processing

suppose i have text file with invoice details in it . I want to extract only some information based on my certain condition such as Mobile - 25,000 and quantity - 1 i want to extract only mobile and ...
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Taking huge time to execute piepeline text classification model using sklearn?

I have created a pipeline model for text classification using python ,Firstly i have tried on 30k records dataset it is working fine got the good results , but when it comes to huge data set like 50k ...
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Looking for suggestions on performing Sementic Analysis of ASR text

Currently I am working on a project where I have ASR on which I am performing semantic analysis to extract meaning out of it. The ASR text contains huge amount of vague conversational text which needs ...
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How to identify word in a sentence representing the song genre?

I am training a model to identify a word that represents a song genre given a sentence. For example, the model is given a sentence "Beethoven songs are part of the classical genre." The model will ...
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Train a deep learning model in chunks/sequentially to avoid memory error

How do I train/fit a model in chunks so as to escape the dreaded memory error? ...
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Using transformers for information extraction

Task I am trying to do some information extraction on earnings reports. I am trying to extract certain metrics, e.g. net sales for quarters. The earnings reports differ quite a lot in how they are ...
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Feeding XLM-R embeddings to neural machine translation?

I’m very new to the filed of deep learning. My aim is to make a translation between Catalan to Catalan Sing Language. The grammar of the two languages is different (e.g Input-> He sells food. Output (...
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Calculating only document frequency or only term frequency from TF-IDF

I have a large corpus of documents (multiple sentences per document), and am trying to find words that appear in some majority of documents (to then filter them out of a future analysis). Since I'm ...
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Flair Custom NER

I'm working on a problem in the domain of NER. I have a dataset wherein I need to have custom tags for different entities. I don't know how to start or even where to start. I know that there are ...
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Practical example and working of Laplace Smoothing or Linear Interpolation in Natural Language Processing (NLP)

Let us suppose we have a document where total_words = 50 (for example -> is,the,now,is,am,here,now) total_unique_words = 40 (for example -> is,the,am,here,now) How can we apply the ...
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How to perform topic modelling on query search results

How can I model topics in the results returned by a search engine with higher weightage to documents ranked higher in the result set? The use case that I am looking at involves extracting the most ...
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How to generalize comments using NLP

I have list of log comments in CSV file. I want to cluster those log comments using K-Means and after that I want convert each cluster comments into general form. for eg. I have bunch of comments in ...
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How to vectorise a network as input to a neural network

I am doing Natural language processing.My input is instructions from customers : "e.g may i know the prices of your teddy bears" Or could i buy this product that looks like a horse." . I want the ...
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SpaCy machine learning model is capturing longer entities partially. How to resolve it?

I have trained a spaCy model on my data using pre-existing en_core_web_sm-2.2.0 model. There are entities in my data which the trained model captures partially. ...
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1answer
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The meaning of random word dropout in NLP

I have been reading the early paper on pre-training in NLP (https://arxiv.org/abs/1511.01432) and I can't understand what random word dropout means. The authors completely ignore explaining this ...
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What is the bleu score of professional human translators?

Machine translation models are usually evaluated using bleu score. I want to get some intuition for this score. What is the bleu score of professional human translator? I know it depends on the ...
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Creating pronunciation dictionary for ASR

I am working on ASR(automatic speech recoginition) on Somali data as master thesis and now I am stuck with how to create a phonetics or pronunciation dictionary for it. I searched over net and could ...
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What are the elements in a BERT word embedding?

As far as I understand, BERT is a word embedding that can be fine-tuned or used directly. With older word embeddings (word2vec, Glove), each word was only represented once in the embedding (one ...
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Building a search tool and classifying text using NLP and ML

Im a newbie in information Retrieval. Currently Im reading a book entitled "An Introduction to Information Retreival" by Christopher D. Manning and Prabhakar Raghavan. Im trying to implement an ai ...
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What is a 'hidden state' in BERT output?

I'm trying to understand the workings and output of BERT, and I'm wondering how/why each layer of BERT has a 'hidden state'. I understand what RNN's have a 'hidden state' that gets passed to each ...
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Extracting name, date and total from a set of heterogeneous receipts

So, this is how the problem goes: I am trying to extract information from scanned receipts like this, What I have been told is that I would get the textual data from a OCR software, so in short I ...
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What could be proper terms for a research direction in natural language processing to measure meaningfulness?

For some time, I did assessments to design metrics on how to recognize well-written and meaningful software requirements. Then I decided to work with Stack Overflow question posts because they are a ...
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The differences between BNf and JSGF in NLP?

I wonder what the differences are between the BNF(Backus-Naur Form) and JSGF(Java Speech Grammar Format)? The former is a kind of context-free grammar taught in CS224, but I learned that the JSGF is ...
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321 views

How to calculate perplexity in PyTorch?

I am wondering the calculation of perplexity of a language model which is based on ...
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358 views

Why is the decoder not a part of BERT architecture?

I can't see how BERT makes predictions without using a decoder unit, which was a part of all models before it including transformers and standard RNNs. How are output predictions made in the BERT ...
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What are x variable and y variable in word2vec model if it is supervised learning

What are x variable and y variable in word2vec model if it is supervised learning. In both the flavours- CBOW and skip-gram model. Though some blogs have explained it as unsupervised learning. ...
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What's wrong with RF/SVM with word embedding (GloVe)?

I searched many times in google for examples on word embedding (specifically GloVe) with Random forest and I couldn't find any single example. For GloVe, it was all either LSTM or CNN. Maybe there's ...
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what are the steps to train BertForMaskedLM model on custom corpus and load it again and test it on new sentences?

what are the steps to train BertForMaskedLM model on custom corpus and load it again and test it on new sentences? I followed the instructions shared in BER github page to train a language model "...
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NL2SQL, for real industrial application, what strategy to locate the exact table?

The datasets like WikiSQL is that the table corresponding to question is given. But in real industrial application, we have 100+ tables for 1 new question. Thank you!
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Are there some research papers about text-to-set generation?

I have googled but find no results. Text-to-(word)set generation or sequence-to-(token)set generation. For example, input a text and then output the tags for this text: ...
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NLP and one-class classifier building

I have a big dataset containing almost 0.5 billions of tweets. I'm doing some research about how firms are engaged in activism and so far, I have labelled tweets which can be clustered in an activism ...
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where to start in natural language processing for a language

My native language is a regional language and few people speak it. I have some assignements in a machine learning course and i was thinking about doing some natural languge processing on my native ...
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Has this method of NLP processing with neural networks been done?

Take the sentence: If you see a green light then you may cross the road. I propose a neural network which produces as output from this sentence 3 masks and a ...
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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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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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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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Looking for a causality to effect dataset

I am looking for a causality dataset that would look like 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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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 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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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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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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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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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 ...