Category "nlp"

How to split a Thai sentence, which does not use spaces, into words?

How to split word from Thai sentence? English we can split word by space. Example: I go to school, split = ['I', 'go', 'to' ,'school'] Split by looking only s

How to split a Thai sentence, which does not use spaces, into words?

How to split word from Thai sentence? English we can split word by space. Example: I go to school, split = ['I', 'go', 'to' ,'school'] Split by looking only s

Does Fine-tunning Bert Model in multiple times with different dataset make it more accuracy?

i'm totally new in NLP and Bert Model. What im trying to do right now is Sentiment Analysis on Twitter Trending Hashtag ("neg", "neu", "pos") by using DistilBer

Tensorflow seq2seq - keep max three checkpoints not working

I am writing a seq2seq and would like to keep only three checkpoints; I thought I was implementing this with: checkpoint_dir = './training_checkpoints' checkpoi

why do pooler use tanh as a activation func in bert, rather than gelu?

class BERTPooler(nn.Module): def init(self, config): super(BERTPooler, self).init() self.dense = nn.Linear(config.hidden_size, config.hidden_size) self.activati

Tensorflow's seq2seq: tensorflow.python.framework.errors_impl.InvalidArgumentError

I am following quite closely the Seq2seq for translation tutorial here https://www.tensorflow.org/addons/tutorials/networks_seq2seq_nmt#define_the_optimizer_and

KALDI: steps/make_mfcc.sh: no such file conf/mfcc.conf

I am very new to kaldi this is probably my own mistake any help is very much appreciated. I am working with my own dataset. I have cloned voxforge setup and use

Parsing HTML into sentences - how to handle tables/lists/headings/etc?

How do you go about parsing an HTML page with free text, lists, tables, headings, etc., into sentences? Take this wikipedia page for example. There is/are: fr

frequency of words in text not present in another text with tf.Tokenizer

I have a text A and a text B. I wish to find the percentage of words in text B (counting all occurrences) not present in the vocabulary (i.e., the list of all u

How do I find most frequent words by each observation in R?

I am very new to NLP. Please, don't judge me strictly. I have got a very big data-frame on customers' feedback, my goal is to analyze feedbacks. I tokenized wo

TypeError: add() takes exactly 2 positional arguments (3 given)

Why I am getting this error Can anyone tell please or explain me how to use it using simple example ------------------------------------------------------------