Automation of the Spoken Poetry Rhyming Game in Persian

This paper aims to investigate how a Persian spoken poetry game, called Mosha'ere, can be computerized by using a Persian automatic speech recognition system trained with read speech. To do this, the text and recitation speech of the poetries of the great poets, Hafez and Sa'di, were gathered. A spoken poetry rhyming game called Chakame, was developed. It utilizes a context-dependent tri-phone HMM acoustic modeling trained by Persian read speech with normal speed to recognize beyts, i.e., lines of verses, spoken by a human user. Chakame was evaluated against two kinds of recitation speech: 100 beyts recited formally at the normal rate and another 100 beyts recited emotionally hyperarticulated at a slow rate. About 23% difference in WER shows the impact of the intrinsic features of emotional recitation speech of verses on recognition rate. However, an overall beyt recognition rate of 98.5% was obtained for Chekame

Introducing a probabilistic–structural method for grapheme-to-phoneme conversion in Persian

Persian writing system deviates from the ideal one due to the lack of one-to-one correspondence between graphemes and phonemes. The present study deals with this question that in spite of the absence of short vowels in Persian writing system and one-to-many and many-to-one relationships between the graphemes and phonemes, how can Persian speakers read out of vocabulary words? This study introduces a probabilistic- structural method that Persian speakers use to read out of vocabulary words in which structural information (including Persian morphology and morphophonemic rules) as well as Arabic morphological templates are considered. In order to test how the introduced method works, Persian speakers were asked to read a list of out of vocabulary words. The mentioned list was used by ID3 and MLP (two methods which are used in machine learning) as input, then the outputs of the method and those of ID3 and MLP were compared with Persian speakers` pronunciations the results proved that the introduced method functions similar to Persian speakers in reading out of vocabulary words

A Critique of the Distinction between Nominal Genitives and Attributive Genitives

Tabibzadeh and Baradaran Hemmati (2015) argue that the Persian Genitive constructions can be divided into attributive genitives and nominal genitives based on six criteria including the possibility of displacing the nominal and attributive dependents, adding the plural suffix, and the possibility of scrambling or topicalization. Attributive genitives can both precede and follow adjectives. Nominal genitives, on the other hand, do not precede adjectives except for the cases that result in a meaning shift or ungrammaticality of noun phrases. They emphasize a peculiar characteristic of Persian Ezafe constructions, but they are not successful in providing a proper explanation of it. In this article, we attempt to provide a brief account of their position, show some mistakes in their syntactic arguments, and criticize the difference between attributive genitives and compound nouns

The Persian pitch accent and its retention after the focus

Abstract Persian words have prominence on the last syllable. Right-edge clitics fall outside this word domain, and segmentally identical words and word-plus-clitic combinations therefore contrast for the location of the prominence. Two experiments were conducted to answer two questions. A production experiment addressed the question whether any phonetic cues other than f0 signal this prominence contrast. We found small phonetic differences between members of minimal pairs outside the more evident f0 differences, but attribute these to side effects of pitch accent placement. The second question was whether post-focal words undergo deaccentuation, as evidenced by neutralization of the contrast between post-focal words and word-plus-clitic combinations. Both the production experiment and a perception experiment showed that there is Post Focus Compression, since pitch excursions in the post-focal speech were considerably reduced, both in interrogative and in declarative utterances, as compared to other positions in the sentence. However, no neutralization occurred. We tentatively conclude that Persian word prominences are pitch accents and that words are not deaccented when the pitch range is reduced after the focus

The Acoustic Analysis of Voice Onset Time in Cochlear Implanted Children and Normal-Hearing Controls

Background and Aim: Hearing has an important role in speech production and making phonological distinction, especially voicing distinction. Voice onset time (VOT) has been a reliable acoustic cue of voicing differences in plosive consonants. The purpose of this study was to measure VOT in initial Persian (Farsi) oral plosives produced by cochlear implanted children, comparing to normal hearing children. Methods: In this cross-sectional study, 20 cases and 20 controls were assessed. Cases were prelingually deaf children who were cochlear implanted 4.5 years prior to test. Controls were normal hearing children at 4.5 years of age. VOT were measured while children uttered oral plosives. The effect of hearing status, voicing, and gender on VOT were assessed. Results: The amount of VOT of plosives produced by girls was higher than boys, in both groups. This difference was significantly higher in voiceless plosives than in voiced ones. In both groups, voiceless plosives had long-positive VOT value; while the amount of VOT was short-positive regarding voiced plosives. Conclusion: It was demonstrated that VOT is significantly correlated with voicing. In voiceless plosives, VOT could not be considered as a phonetic correlate of hearing status; whereas it made significant differences between cochlear implanted children and hearing controls. Furthermore, it was confirmed that concerning voiceless plosives, the amount of VOT of girls was significantly higher than boys. On the contrary, in voiced plosives, gender had no significant effect on the amount of VOT

Acoustic Parameters in Persian-Speaking Patients with Dysphonia

Background & Objectives: Studying voice acoustic parameters in vowel production is a crucial component of every standard voice evaluation. Voice Analysis is non-invasive. Nowadays, computerized Voice Analysis is growing rapidly. Therefore, understanding acoustic parameters in healthy and unhealthy individuals is more significant than before. This research is a step toward boosting our knowledge about voice acoustic parameters. The main purpose of this research is to study acoustic characteristics in dysphonic and healthy Iranian individuals.  Methods: The current study was descriptive-analytic. Vowel Analysis was conducted through Praat software. Voices of 50 dysphonic patients and 50 healthy participants were evaluated. The acoustic parameters included average, standard deviation, and range of fundamental frequency, jitter, shimmer, the number and degree of voice breaks, and harmonic to noise ratio. Results: In all studied acoustic characteristics, patients’ mean scores were higher than controls’ mean scores, except for harmonic to noise ratio which was higher in the healthy individuals. Although, the number of voice breaks in healthy male and female population was zero, it was 1.8 in male patients and 4.4 in female patients (P<0.05). jitter and shimmer in patients were dramatically higher (P<0.05) than their amount in healthy controls; moreover, patients’ fundamental frequency range (male: 54.6±59.0, female: 78.6±68.4) was extremely broader than individuals with normal voices (male: 9.7±4.1, female: 16.2±7.3). Conclusion: It was clarified that there are considerably significant differences in some acoustic features. These differences may be used as a foundation for diagnosis and intervention in dysphonic patients. This study illustrated that Acoustic Analysis can differentiate healthy individuals from patients. Hence, it can be used as a non-invasive, fast and accurate method