Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Code-Switching Detection with Data-Augmented Acoustic and Language
  Models   In this paper, we investigate the code-switching detection performance of a
code-switching (CS) automatic speech recognition (ASR) system with
data-augmented acoustic and language models. We focus on the recognition of
Frisian-Dutch radio broadcasts where one of the mixed languages, namely
Frisian, is under-resourced. Recently, we have explored how the acoustic
modeling (AM) can benefit from monolingual speech data belonging to the
high-resourced mixed language. For this purpose, we have trained
state-of-the-art AMs on a significantly increased amount of CS speech by
applying automatic transcription and monolingual Dutch speech. Moreover, we
have improved the language model (LM) by creating CS text in various ways
including text generation using recurrent LMs trained on existing CS text.
Motivated by the significantly improved CS ASR performance, we delve into the
CS detection performance of the same ASR system in this work by reporting CS
detection accuracies together with a detailed detection error analysis.

34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics