Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR Export

@article{citeulike:6079809, abstract = {This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as /@?/ can drop below 35\% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research.}, author = {Alotaibi, Y. A. and Muhammad, G.}, citeulike-article-id = {6079809}, citeulike-linkout-0 = {http://www.worldcat.org/oclc/444423077}, journal = {Computer Speech \& Language}, keywords = {arabic, language}, number = {2}, pages = {219--231}, posted-at = {2009-11-06 03:11:17}, priority = {2}, title = {Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR}, url = {http://www.worldcat.org/oclc/444423077}, volume = {24}, year = {2010} }

TY - JOUR ID - citeulike:6079809 L3 - citeulike-article-id:6079809 N2 - This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as /@?/ can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research. IS - 2 JF - Computer Speech & Language EP - 231 TI - Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR VL - 24 SP - 219 KW - arabic KW - language AU - Alotaibi, YA AU - Muhammad, G PY - 2010/// UR - http://www.worldcat.org/oclc/444423077 ER -