We present the results of the VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects, which we organized as part …
In this paper we present the experiments and results by the SUKI team in the German Dialect Identification shared task of the VarDial 2018 Evaluation Campaign. Our submission …
This article describes an unsupervised language model (LM) adaptation approach that can be used to enhance the performance of language identification methods. The approach is …
A Hanani, R Naser - Natural Language Engineering, 2020 - cambridge.org
This paper describes our automatic dialect identification system for recognizing four major Arabic dialects, as well as Modern Standard Arabic. We adapted the X-vector framework …
S Shon, A Ali, J Glass - 2017 ieee automatic speech …, 2017 - ieeexplore.ieee.org
In order to successfully annotate the Arabic speech content found in open-domain media broadcasts, it is essential to be able to process a diverse set of Arabic dialects. For the 2017 …
This paper describes an Arabic Automatic Speech Recognition system developed on 15 hours of Multi-Genre Broadcast (MGB-3) data from YouTube, plus 1,200 hours of Multi …
Arabic dialect identification is a specific task of natural language processing, aiming to automatically predict the Arabic dialect of a given text. Arabic dialect identification is the first …
In this paper we present the GDI_classification entry to the second German Dialect Identification (GDI) shared task organized within the scope of the VarDial Evaluation …
Abstract Arabic Dialect Identification is the process of identifying the speaker's dialect based on several features in the corresponding acoustic wave. In this research, machine learning …