Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Word Level Language Identification in English Telugu Code Mixed Data   In a multilingual or sociolingual configuration Intra-sentential Code
Switching (ICS) or Code Mixing (CM) is frequently observed nowadays. In the
world, most of the people know more than one language. CM usage is especially
apparent in social media platforms. Moreover, ICS is particularly significant
in the context of technology, health, and law where conveying the upcoming
developments are difficult in one's native language. In applications like
dialog systems, machine translation, semantic parsing, shallow parsing, etc. CM
and Code Switching pose serious challenges. To do any further advancement in
code-mixed data, the necessary step is Language Identification. In this paper,
we present a study of various models - Nave Bayes Classifier, Random Forest
Classifier, Conditional Random Field (CRF), and Hidden Markov Model (HMM) for
Language Identification in English - Telugu Code Mixed Data. Considering the
paucity of resources in code mixed languages, we proposed the CRF model and HMM
model for word level language identification. Our best performing system is
CRF-based with an f1-score of 0.91.

25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph