Syllabification Of Words Research Articles

Morphological and Semantical Effects of Phonemes on Pashto Lexical Structures

Phonemes and segments are the key elements in the structure of Pashto words, playing an important role similar to other languages worldwide. Through the combination and arrangement of these segments, numerous morphemes and diverse words are generated. When assigning a vowel or consonant to the origin or base form of a word, it leads to the creation of new words and constructions that possess different forms, meanings, and belong to various grammatical categories. Structurally, at least one, two, three, or a maximum of four bound morphemes in the form of segments or phonemes could be added to the root or base morpheme, thus generating new lexemes and words. The addition of new phonemes and segments to the base or root form of a word alters its case, identification, quality, quantity, gender, number, tense, modification, meaning, and grammatical classification. Another important role of segments in the structure of lexemes is the syllabification of simple and complex words. The accumulation of each phoneme brings changes in the number of syllables within that word or phrase. Vowel segments primarily contribute to the syllabification of words. In conclusion, the hierarchical arrangement of segments generates new morphemes, while the combination of bound and free morphemes forms the basis for creating new simple, compound, and complex words in the Pashto language.

Unusual Syllabification Among Nollywood Actors: A Perceptual Analysis

This study examines the unusual syllabification among the Nollywood actors in their use of English while acting in various movies. The main purpose is to examine the cause of unusual syllabification that is usually observed among Nollywood actors. To carry out this analysis, a case study approach was used in the study and data were collected through playing and watching the movies. Attention was paid to unusual syllabification of words of different syllables by some actors. These words were jotted down and later analyzed by comparing them with actual syllabification using Longman Dictionary of Contemporary English which acts as the control. The theoretical framework used for the study is prominence/Sonority Theory with special emphasy on Sonority Sequencing Principles (SSP). Our finding revealed that there are instances of unusual syllabification of words by Nollywood actors. Keywords: Nollywood, Prominence Theory, Syllables, Syllabification. DOI: 10.7176/JLLL/77-08 Publication date: March 31 st 2021

Syllabification Model of Indonesian Language Named-Entity Using Syntactic n-Gram

Abstract Syllabication or syllabification is an activity to detect syllable boundaries in a word. There are two main ways for automatic syllabification, namely rule-based and data-driven. The rule-based approach is based on the general principle of syllabification, while the data-driven method uses a set of syllabified words to create a syllabification of unknown words. Research on syllabification of words has been done a lot. However, most of these studies only deal with the formal words but still a few studies for named entities. Besides, named entities tend to be more complicated than the regular words. In this research, a syntactic n-Gram is proposed and investigated to syllabify the named entities since it is developed based on the n-gram that has an excellent accuracy and tends to be consistent with various languages. Evaluation on 20 k named-entities based on 4-fold cross-validation show that the proposed model gives a competitive syllable error rate (SER) compare to another similar n-gram-based model.

Syllabification of English Words by Pashto Speakers

Syllabification of words plays a vital role in learning native like pronunciation. The present study tried to explore the syllabification of English words by Pashto speakers. The study aimed to put light on the problematic areas for Pashto speakers in terms of syllabification of English words. The data was collected from twenty undergraduate students and analyzed with reliable scientific tools. The analyzed data proved that English words having triphthongs were problematic for Pashto speakers. In addition to it, words having syllabic consonants were also problematic for Pashto speakers. Furthermore, words containing x in spelling also proved to be problematic for Pashto speakers. English words having the syllable structure CVC.VC were incorrectly syllabified CV.CVC. Pashto speakers faced problems in the identification of syllable boundaries in words where consonant clusters are used. The study recommends that Pashto speakers need proper training for learning correct syllabification of English words.

Syllabification of Balinese Words Using the Syllabification Algorithm

Abstract
 This research discusses the syllabification of Balinese words. The syllabification of Balinese words is necessary in determining padalingsa in pupuh. In order to be able to develop the application of technology in the field of pupuh literary, a system that can automatically find the correct division of a Balinese word into syllabels is required. Several studies have been conducted on the syllabification Spanish and Sinhala language using rule-based approach. Both of the studies achieved good accuracy score. Thus, in this research we apply the rule-based syllabification approach on Balinese words. The data used in this study were 257 Balinese words in which the system managed to correctly divide the word as many as 244 and obtained an accuracy score of 94.94%.
 Keywords: Syllabification Algorithm, Word, Balinese, Word Syllabification, Rule-based

Phonological strategies and peer scaffolding in digital literacy game-playing sessions in a Finnish pre-primary class

This study explored what kinds of phonological strategies are used by children and how they scaffold each other while they solve tasks in a digital literacy game. The theoretical basis of this study lies in Vygotsky's thoughts on the role of social interaction in learning and in the concept of peer scaffolding. The data included eight videotaped game-playing sessions conducted in small groups in a Finnish pre-primary class with six-year-old children. The analysis was carried out in two phases. Based on a qualitative content analysis of peer-scaffolding episodes (N = 363), it was found that the Finnish-speaking children used several types of phonological strategies, such as the syllabification of words, phonological processing and the production of letter names in solving word- and syllable-level game tasks. Furthermore, a microgenetic analysis of the episodes showed that the six-year-olds displayed emerging peer-scaffolding patterns, such as initiation, responding, modelling and expanding. The results illustrate the pedagogical potential of digital literacy games in the context of social interaction and peer scaffolding.

An Improved Syllabification for a Better Malay Language Text-to-Speech Synthesis (TTS)

Text-to-speech (TTS) is an important component of robots, humanoids and Internet of Things as a mean of human computer interaction. One of the main components of TTS is text processing that functions as the producer of syllabic speech units to be used in the generation of human-like speech. The naturalness of TTS largely depends on text processing component, particularly word syllabification. Syllabification is a process of segmenting the given text input into sequence syllabic speech units. This paper begins with investigations of previous syllabification technique of Malay language to identify the limitations. An improved syllabification technique is then proposed and compared against the performance of another three known syllabifications. The datasets used comprises 25,000 words collected from Malay language online national newspaper articles and Wikitionary Open Content Dictionary. Word Error Rate (WER) percentage is calculated and our proposed syllabification technique achieved the lowest WER of 2.61% with an accuracy rate of 97.39%.

Automatic Syllabification in English: A Comparison of Different Algorithms

Automatic syllabification of words is challenging, not least because the syllable is not easy to define precisely. Consequently, no accepted standard algorithm for automatic syllabification exists. There are two broad approaches: rule-based and data-driven. The rule-based method effectively embodies some theoretical position regarding the syllable, whereas the data-driven paradigm tries to infer "new" syllabifications from examples assumed to be correctly syllabified already. This article compares the performance of several variants of the two basic approaches. Given the problems of definition, it is difficult to determine a correct syllabification in all cases and so to establish the quality of the "gold standard" corpus used either to evaluate quantitatively the output of an automatic algorithm or as the example-set on which data-driven methods crucially depend. Thus, we look for consensus in the entries in multiple lexical databases of pre-syllabified words. In this work, we have used two independent lexicons, and extracted from them the same 18,016 words with their corresponding (possibly different) syllabifications. We have also created a third lexicon corresponding to the 13,594 words that share the same syllabifications in these two sources. As well as two rule-based approaches (Hammond's and Fisher's implementation of Kahn's), three data-driven techniques are evaluated: a look-up procedure, an exemplar-based generalization technique, and syllabification by analogy (SbA). The results on the three databases show consistent and robust patterns. First, the data-driven techniques outperform the rule-based systems in word and juncture accuracies by a very significant margin but require training data and are slower. Second, syllabification in the pronunciation domain is easier than in the spelling domain. Finally, best results are consistently obtained with SbA.

Framework for Choosing a Set of Syllables and Phonemes for Lithuanian Speech Recognition

This paper describes a framework for making up a set of syllables and phonemes that subsequently is used in the creation of acoustic models for continuous speech recognition of Lithuanian. The target is to discover a set of syllables and phonemes that is of utmost importance in speech recognition. This framework includes operations with lexicon, and transcriptions of records. To facilitate this work, additional programs have been developed that perform word syllabification, lexicon adjustment, etc. Series of experiments were done in order to establish the framework and model syllable- and phoneme-based speech recognition. Dominance of a syllable in lexicon has improved speech recognition results and encouraged us to move away from a strict definition of syllable, i.e., a syllable becomes a simple sub-word unit derived from a syllable. Two sets of syllables and phonemes and two types of lexicons have been developed and tested. The best recognition accuracy achieved 56.67% ±0.33. The speech recognition system is based on Hidden Markov Models (HMM). The continuous speech corpus LRN0 was used for the speech recognition experiments.

Word syllabification in speech synthesis system

The present invention relates to a system and method of word syllabification. The present invention receives a word to be syllabified and determines therefrom all possible substrings capable of forming part of the word. Sequences matching at least part of or the whole of the word are determined from the substrings together with respective probabilities of occurrence and the sequence having the greatest probability of occurrence is selected as being the most probable syllabification of the word. The most probable sequence can be determined in many different ways. For example, the sequence can be determined by commencing with the substring having the greatest probability of forming the beginning of a given word and subsequently traversing in a step-by-step manner a table comprising all possible substrings of the word and at each step selecting the next substring of the sequence according to which of the possible next substrings has the highest probability of occurrence. A further method of determining the most probable sequence would be to adopt the above step-by-step approach for all possible substrings capable of forming the beginning of the given word. Alternatively, all possible sequences of substring capable of constituting the word can be determined together respective probabilities of occurrence thereof and the sequence having the highest respective probability of occurrence is selected as being the most probable syllabification of the given word.

Crossing word boundaries : constraints for misaligned syllabification

In this work, I examine a set of languages which appear to require resyllabification postlexically; in less derivational terms, a word's syllabification in isolation differs from its syllabification in a phrase-internal context. Although many people, myself included, have been looking at such cases in isolation over the years, I bring together several examples here to see what features they share and how an Optimality Theory analysis improves upon rule-based derivational approaches.