Computational Restrictions on Interative Prosodic Processes

We demonstrate a computational restriction on iterative prosody in phonology by using logical transductions. We show that the typology is fundamentally local but requires output recursion, formulated via quantifier-free transductions and least-fixed-point operators, respectively. We focus on two case studies from iterative prosody. One is iterative secondary stress. The other is more complex: iterative syllabification and epenthesis in Arabic dialects. The second case study involves formalizing Ito (1989)'s analysis of directional syllabification.

Secondary Stress Weighting Factor and Plastic Reduction Factor of Surface Cracked Pipes Under Bending

In piping design analysis, the secondary stresses (displacement controlled) may have different design limits than primary stresses (load-controlled stresses). The current design limits for secondary stresses are based on elastic stress analysis. But realistically a flaw in the piping system can cause non-linear behavior due to the plasticity at the crack plane as well as in the adjacent uncracked-piping material. Hence, the actual stresses in a cracked piping system which are elastic-plastic are different than the design stresses which are elastically calculated. To assess margins in the secondary stresses calculated using elastic stress analysis, two parameters are defined in this paper. The first one is the Secondary Stress Weighting Factor (SSWF) on total stress which is defined as the ratio of actual elastic-plastic stresses in a system to the elastic design stress. An alternative approach to applying margins on secondary stresses is to a use a reduction factor only on stresses above the yield stress. This reduced factor is called Plastic Reduction Factor (PRF). In this paper, a methodology developed to determine these factors for circumferential surface-cracked TP304 stainless steel pipes subjected to bending loads at room temperature is described. Four-point-bend tests are conducted on pipes with varying circumferential surface-crack lengths and depths. The moment and rotations needed for the pipe failure for different crack sizes are determined and compared to elastically calculated moments and rotations to establish margins.

Word Stress system of the Saraiki language

This study presents an Optimality-Theoretic analysis of Saraiki word stress. This study presents a first exploration of word stress in the framework of OT. Words in Saraiki are mostly short; secondary stress plays no role here. Saraiki stress is quantity-sensitive, so a distinction must be made between short and long vowels, and light and heavy syllables. A metrical foot can consist of one heavy syllable, two light syllables, or one light and one heavy syllable. The Foot structure starts from right to left in prosodic words. The foot is trochaic and the last consonant in Saraiki words is extra metrical. These generalizations are best captured by using metrical phonology first and Optimality constraints later on.

Accent labeling algorithm based on morphological rules and machine learning in English conversion system

The dependency of a speech recognition system on the accent of a user leads to the variation in its performance, as the people from different backgrounds have different accents. Accent labeling and conversion have been reported as a prospective solution for the challenges faced in language learning and various other voice-based advents. In the English TTS system, the accent labeling of unregistered words is another very important link besides the phonetic conversion. Since the importance of the primary stress is much greater than that of the secondary stress, and the primary stress is easier to call than the secondary stress, the labeling of the primary stress is separated from the secondary stress. In this work, the labeling of primary accents uses a labeling algorithm that combines morphological rules and machine learning; the labeling of secondary accents is done entirely through machine learning algorithms. After 10 rounds of cross-validation, the average tagging accuracy rate of primary stress was 94%, the average tagging accuracy rate of secondary stress was 94%, and the total tagging accuracy rate was 83.6%. This perceptual study separates the labeling of primary and secondary accents providing the promising outcomes.