Name
Abstract | ||
|---|---|---|
We study the effectiveness of recently developed language recognition techniques based on speech recognition models for the discrimination of Arabic dialects. Specifically, we investigate dialect-specific and cross-dialectal phonotactic models, using both language models and support vector machines (SVMs). Techniques are evaluated both alone and in combination with a cepstral system with joint factor analysis (JFA), using a four-dialect data set employing 30-second telephone speech samples. We find good complementarity from different features and modeling paradigms, and achieve 2% average equal error rate for pairwise classification. |
Year | Venue | Field |
|---|---|---|
2011 | 12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | Phonotactics,Arabic,Computer science,Linguistics |
DocType | Citations | PageRank |
Conference | 7 | 0.59 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Murat Akbacak | 1 | 86 | 9.86 |
| Dimitra Vergyri | 2 | 373 | 36.97 |
| Andreas Stolcke | 3 | 6690 | 712.46 |
| Nicolas Scheffer | 4 | 354 | 23.77 |
| Arindam Mandal | 5 | 158 | 16.44 |