This study was concerned with the short vowels in modern standard Arabic words with Consonant Vowel-Consonant Vowel-Consonant Vowel (CVCVCV) structure, and the long vowels in words with Consonant Vowel Vowel-Consonant...This study was concerned with the short vowels in modern standard Arabic words with Consonant Vowel-Consonant Vowel-Consonant Vowel (CVCVCV) structure, and the long vowels in words with Consonant Vowel Vowel-Consonant (CVVC). Even though there has been a dispute on the precise number of Arabic vowels that exist between language studies, this study used the opinion that the Arabic language has three vowels;the elongation of each vowel gave the other three because this is the opinion of classical Arabic linguists which is the source of the Modern Standard Arabic (MSA). Studies said that the first and second formant values (F1, F2) can represent the vowels. In this study, the formants were measured using LPC (Linear Predictive Coding), verifying the measurement to see if the measured follows the pattern of formants measurements of the other studies, and the formants were used to investigate the relationship between short and long vowels. Furthermore, the study figured out if the dialect of speakers can affect the values of formants, even if the spoken language is MSA, some statistical measurements were calculated to evaluate the relationship.展开更多
Arabic texts suffer from missing short vowels. Arabic Speech Recognition is not as good as English speech recognition due to the short vowels not being recognized. And the Arabic language is unlike the English languag...Arabic texts suffer from missing short vowels. Arabic Speech Recognition is not as good as English speech recognition due to the short vowels not being recognized. And the Arabic language is unlike the English language in characteristics such as the number of vowels. English has more than 24 vowels that are close to each other in pronunciation. The Arabic language only has three short vowels that are far from each other in utter and measurement, by elongating those short vowels, long vowels arose. Researchers said that the vowels could be recognized using formants. The formants’ measurements of Arabic vowels are far from each other too, so it is possible to recognize them so that Arabic Speech recognition can give more accurate results. The paper applies this idea to the corpus Phonemes of Arabic. It uses the Euclidian distance method to measure the distances between formant values to recognize Arabic from words with a CV3 structure, the Linear Predictive Coding method and MATLAB to develop the programs that will extract the formants and calculate the means of the short vowels by using the corpus to identify the short vowels within words in the corpus. The results showed that if highly qualified readers were chosen to read the Arabic text, then higher rates of recognition of the short vowels involved in words will be achieved. This paper revealed that some of the characteristics of a language can be utilized for vowel recognition or to enhance the existing methods for speech recognition.展开更多
本文借助超声仪采集了藏语安多方言元音的生理语音数据,系统分析了安多方言元音的动态舌位和稳定段的静态舌位,以及声学共振峰数据。实验结果显示,在舌位运动过程中确实存在一个稳定阶段,此阶段各帧数据间的差异都较小,将该阶段的舌位...本文借助超声仪采集了藏语安多方言元音的生理语音数据,系统分析了安多方言元音的动态舌位和稳定段的静态舌位,以及声学共振峰数据。实验结果显示,在舌位运动过程中确实存在一个稳定阶段,此阶段各帧数据间的差异都较小,将该阶段的舌位特征与古藏语相比,发现安多方言元音系统已经产生了一定的变化,即元音舌位由低到高依次为/a/、/i, u, o/、/e/,舌位由前到后分别为/e/、/i, u, a/、/o/,其中元音/i/和/u/央化并产生了新的音位变体。最后我们从空间域角度对安多方言元音的舌体音姿进行了总体描述。明确了元音在生理特征与声学特征上具有统一性,这对藏语不同方言之间的发音差异和共性研究均有一定的理论意义和参考价值。展开更多
文摘This study was concerned with the short vowels in modern standard Arabic words with Consonant Vowel-Consonant Vowel-Consonant Vowel (CVCVCV) structure, and the long vowels in words with Consonant Vowel Vowel-Consonant (CVVC). Even though there has been a dispute on the precise number of Arabic vowels that exist between language studies, this study used the opinion that the Arabic language has three vowels;the elongation of each vowel gave the other three because this is the opinion of classical Arabic linguists which is the source of the Modern Standard Arabic (MSA). Studies said that the first and second formant values (F1, F2) can represent the vowels. In this study, the formants were measured using LPC (Linear Predictive Coding), verifying the measurement to see if the measured follows the pattern of formants measurements of the other studies, and the formants were used to investigate the relationship between short and long vowels. Furthermore, the study figured out if the dialect of speakers can affect the values of formants, even if the spoken language is MSA, some statistical measurements were calculated to evaluate the relationship.
文摘Arabic texts suffer from missing short vowels. Arabic Speech Recognition is not as good as English speech recognition due to the short vowels not being recognized. And the Arabic language is unlike the English language in characteristics such as the number of vowels. English has more than 24 vowels that are close to each other in pronunciation. The Arabic language only has three short vowels that are far from each other in utter and measurement, by elongating those short vowels, long vowels arose. Researchers said that the vowels could be recognized using formants. The formants’ measurements of Arabic vowels are far from each other too, so it is possible to recognize them so that Arabic Speech recognition can give more accurate results. The paper applies this idea to the corpus Phonemes of Arabic. It uses the Euclidian distance method to measure the distances between formant values to recognize Arabic from words with a CV3 structure, the Linear Predictive Coding method and MATLAB to develop the programs that will extract the formants and calculate the means of the short vowels by using the corpus to identify the short vowels within words in the corpus. The results showed that if highly qualified readers were chosen to read the Arabic text, then higher rates of recognition of the short vowels involved in words will be achieved. This paper revealed that some of the characteristics of a language can be utilized for vowel recognition or to enhance the existing methods for speech recognition.
文摘本文借助超声仪采集了藏语安多方言元音的生理语音数据,系统分析了安多方言元音的动态舌位和稳定段的静态舌位,以及声学共振峰数据。实验结果显示,在舌位运动过程中确实存在一个稳定阶段,此阶段各帧数据间的差异都较小,将该阶段的舌位特征与古藏语相比,发现安多方言元音系统已经产生了一定的变化,即元音舌位由低到高依次为/a/、/i, u, o/、/e/,舌位由前到后分别为/e/、/i, u, a/、/o/,其中元音/i/和/u/央化并产生了新的音位变体。最后我们从空间域角度对安多方言元音的舌体音姿进行了总体描述。明确了元音在生理特征与声学特征上具有统一性,这对藏语不同方言之间的发音差异和共性研究均有一定的理论意义和参考价值。
