Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 1318–1326 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 1318 Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus Mahmoud El-Haj School of Computing and Communications Lancaster University United Kingdom m.el-haj@lancaster.ac.uk Abstract This paper introduces Habibi the first Arabic Song Lyrics corpus. The corpus comprises more than 30,000 Arabic song lyrics in 6 Arabic dialects for singers from 18 different Arabic countries. The lyrics are segmented into more than 500,000 sentences (song verses) with more than 3.5 million words. I provide the corpus in both comma separated value (csv) and annotated plain text (txt) file formats. In addition, I converted the csv version into JavaScript Object Notation (json) and eXtensible Markup Language (xml) file formats. To experiment with the corpus I run extensive binary and multi-class experiments for dialect and country-of-origin identification. The identification tasks include the use of several classical machine learning and deep learning models utilising different word embeddings. For the binary dialect identification task the best performing classifier achieved a testing accuracy of 93%. This was achieved using a word-based Convolutional Neural Network (CNN) utilising a Continuous Bag of Words (CBOW) word embeddings model. The results overall show all classical and deep learning models to outperform our baseline, which demonstrates the suitability of the corpus for both dialect and country-of-origin identification tasks. I am making the corpus and the trained CBOW word embeddings freely available for research purposes. Keywords: Corpus, Arabic NLP, Language Identification, Classification, Dialect Identification, Deep Learning, Word Embeddings 1. Introduction The Middle East and North Africa (MENA) are now com- manding attention when it comes to the global music in- dustry1. Most importantly, the different territories and the singers emerging from them are already reaping real ben- efit from that attention. The increasing availability of mo- bile data has given rise to a rich and diverse global land- scape with fans in each territory accessing music through a unique and evolving combination of formats and services. With more than 400 million Arabic speakers worldwide, I believe it is of significant value to study the language used in the lyrics of Arabic songs. Lyrics are the words that make up a song and are usually consisting of verses and choruses. Unlike western music, Arabic songs are poorly classified and the majority of the songs available online are classified under either Modern Arabic Pop genre or what is now known as Franco-Arabic, which is a blend of western and eastern music but mainly using Arabic lyrics (Soboh et al., 2017). Arabic genres dif- fer from the western ones (e.g. Rock, Pop, Metal, ...etc) and fall into categories that better describe the region (di- alect or country of origin) of the singer rather than the type of music. This is more common in modern Arabic music (Touma and Touma, 2003). Online music streaming giants such as Spotify2 and Deezer3 follow a similar categorisation by providing music mix …

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