Effects of syllable boundaries in Tibetan reading

Abstract

Interword spaces exist in the texts of many languages that use alphabetic writing systems. In most cases, interword spaces, as a kind of word boundary information, play an important role in the reading process of readers. Tibetan also uses alphabetic writing, its text has no spaces between words as word boundary markers. Instead, there are intersyllable tshegs (“ ”), which are superscript dots. Interword spaces play an important role in reading as word boundary information. Therefore, it is interesting to investigate the role of tshegs and what effect replacing tshegs with spaces will have on Tibetan reading. To answer these questions, Experiment 1 was conducted in which 72 Tibetan undergraduates read three-syllable-boundary conditions (normal, spaced, and untsheged). However, in Experiment 1, because we performed the experimental operations of deleting tshegs and replacing tshegs, the spatial information distribution of Tibetan sentences under different operating conditions was different, which may have a certain potential impact on the experimental results. To rule out the underlying confounding factor, in Experiment 2, 58 undergraduates read sentences for both untsheged and alternating-color conditions. Overall, the global and local analyses revealed that tshegs, spaces, and alternating-color markers as syllable boundaries can help readers segment syllables in Tibetan reading. In Tibetan reading, both spaces and tshegs are effective visual syllable segmentation cues, and spaces are more effective visual syllable segmentation cues than tshegs.

Recognition and Evaluation Algorithm for English Pronunciation Syllables Based on Neural Prediction Model

“…Pahuja H's work was to establish a syllable recognition system using visual speech recognition using convolutional neural networks [9]. Wang D believed that the study of word syllables is crucial in many alphabetic language texts [10]. Therefore, this article hoped to draw on previous research experience to design algorithms for recognizing and evaluating stressed syllables.…”