Speech corpora are key components needed by both: linguists (in language analyses, research and teaching languages) and Natural Language Processing (NLP) researchers (in training and evaluating several NLP tasks such as speech recognition, text-to-speech and speech-to-text synthesis). Despite of the great demand, there is still a huge shortage in available corpora, especially in the case of dialectal languages, and code-switched speech. In this paper, we present our efforts in collecting and analyzing a speech corpus for conversational Egyptian Arabic. As in other multilingual societies, it is common among Egyptians to use a mix of Arabic and English in daily conversations. The act of switching languages, at sentence boundaries or within the same sentence, is referred to as code-switching. The aim of this work is a three-fold: (1) gather conversational Egyptian Arabic spontaneous speech, (2) obtain manual transcriptions and (3) analyze the speech from the code-switching perspective. A subset of the transcriptions were manually annotated for part-of-speech (POS) tags. The POS distribution of the embedded words was analyzed as well as the POS distribution for the trigger words (Arabic words preceding a code-switching point). The speech corpus can be obtained by contacting the authors.
@InProceedings{HAMED18.1046, author = {Injy Hamed and Mohamed Elmahdy and Slim Abdennadher}, title = "{Collection and Analysis of Code-switch Egyptian Arabic-English Speech Corpus}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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