Spoken Arabic Algerian dialect identification

Dialect identification is a challenging task and this becomes more complicated when dealing with under-resourced dialects. In this paper, we propose a system based on prosodic speech information, namely intonation and rhythm for identification of Intra-country dialects. The speech features are extracted after a coarse-grained consonant/vowel segmentation. Dialect models are built using both Deep Neural Networks (DNNs) and SVM. The hyper-parameters for the DNNs topology are tuned using a genetic algorithm. Our framework is implemented and evaluated on KALAM'DZ, a Web-based corpus dedicated to Algerian Arabic Dialectal varieties, with more than 42 h encompassing the four major Algerian subdialects: Hilali, Su-laymite, Ma'qilian, and Algiers-blanks. The results show that the DNNs implementation of Algerian Arabic Dialect IDentification system (a2did) reaches the same results when compared to SVM modeling. In addition, we concluded that a contrastive baseline acoustic-based classification system can serve as a complementary system to our a2did. The overall results reveal the suitability of our prosody-based a2did for speaker-independent dialect identification when utterances size are short. A requirement for real-time applications.

[1]  Julia Hirschberg,et al.  Using prosody and phonotactics in Arabic dialect identification , 2009, INTERSPEECH.

[2]  Rong Tong,et al.  Integrating Acoustic, Prosodic and Phonotactic Features for Spoken Language Identification , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[3]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[4]  Mansour Alsulaiman,et al.  KSU rich Arabic speech database , 2013 .

[5]  Daniel P. W. Ellis,et al.  Dialect and Accent Recognition Using Phonetic-Segmentation Supervectors , 2011, INTERSPEECH.

[6]  Preslav Nakov,et al.  Findings of the VarDial Evaluation Campaign 2017 , 2017, VarDial.

[7]  Alvin F. Martin,et al.  The 2011 NIST Language Recognition Evaluation , 2010, INTERSPEECH.

[8]  Salem Ghazali,et al.  Speech Rhythm Variation in Arabic Dialects , 2002 .

[9]  Andreas Stolcke,et al.  Effective Arabic Dialect Classification Using Diverse Phonotactic Models , 2011, INTERSPEECH.

[10]  Bin Ma,et al.  Spoken Language Recognition: From Fundamentals to Practice , 2013, Proceedings of the IEEE.

[11]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[12]  L William Zartman,et al.  Algeria , 1971, Africa Research Bulletin: Economic, Financial and Technical Series.

[13]  P. Lewis.  Ethnologue : languages of the world , 2009 .

[14]  Soumia Bougrine,et al.  Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties , 2017, WANLP@EACL.

[15]  Adla Abdelkader,et al.  GMM-Based Maghreb Dialect IdentificationSystem , 2015 .

[16]  Fawzi Suliman Alorifi,et al.  Automatic Identification of Arabic Dialects USING Hidden Markov Models , 2008 .

[17]  Abderrahmane Amrouche,et al.  Algerian Modern Colloquial Arabic Speech Corpus (AMCASC): regional accents recognition within complex socio-linguistic environments , 2017, Lang. Resour. Evaluation.

[18]  Inês Salselas,et al.  Music and speech in early development: automatic analysis and classification of prosodic features from two Portuguese variants , 2011 .

[19]  Nizar Habash,et al.  Spoken Arabic Dialect Identification Using Phonotactic Modeling , 2009, SEMITIC@EACL.

[20]  John C. Wells,et al.  Accents of English , 1982 .

[21]  Stephen Taylor,et al.  Palestinian Arabic regional accent recognition , 2015, 2015 International Conference on Speech Technology and Human-Computer Dialogue (SpeD).

[22]  Mahmoud Al-Ayyoub,et al.  Spoken Arabic dialects identification: The case of Egyptian and Jordanian dialects , 2014, 2014 5th International Conference on Information and Communication Systems (ICICS).

[23]  Melissa Barkat-Defradas,et al.  Identification automatique des parlers arabes par la prosodie , 2006 .

[24]  K. Sreenivasa Rao,et al.  Language Identification Using Spectral and Prosodic Features , 2015 .

[25]  William M. Campbell,et al.  Discriminative n-gram selection for dialect recognition , 2009, INTERSPEECH.

[26]  Joseph P. Campbell,et al.  A linguistically-informative approach to dialect recognition using dialect-discriminating context-dependent phonetic models , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[27]  Marc A. Zissman,et al.  Automatic dialect identification of extemporaneous conversational, Latin American Spanish speech , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[28]  K. Versteegh.  The Arabic Language , 1997 .

[29]  Joaquín González-Rodríguez,et al.  On the use of deep feedforward neural networks for automatic language identification , 2016, Comput. Speech Lang..