the smallest structure of a language which makes words, sentences and verses and is the basic element of the quranic miracle is a phoneme. the phonemes are studied in two aspects: 1. each phoneme itself that is concentrated on the qualities and the vent which its sounds out; 2. the combination of the phonemes which is concentrated on the segments, spaces and … the interpreters of the quran have...

Various automated techniques can be used to generalise from phonemic lexicons through the extraction of grapheme-to-phoneme rule sets. These techniques are particularly useful when developing pronunciation models for previously unmodelled languages: a frequent requirement when developing multilingual speech processing systems. However, many of the learning algorithms (such as Dynamically Expand...

This paper describes a trainable method for generating letter to sound rules for the Greek language, for producing the pronunciation of out-of-vocabulary words. Several approaches have been adopted over the years for graphemeto-phoneme conversion, such as hand-seeded rules, finite state transducers, neural networks, HMMs etc, nevertheless it has been proved that the most reliable method is a ru...

Most models of spelling assume that people rely on two procedures when engaging in spelling: a lexical look-up procedure that retrieves spellings in their entirety, and a nonlexical procedure that constructs spellings with a set of phoneme-grapheme rules. In the present research, we investigated whether larger sized subsyllabic relationships also play a role in spelling, and how they compare to...

We’d been studying artificial neural networks(ANNs) that can learn and generate the prosody of a Korean sentence. To hear more natural synthetic speech generated by a Korean TTS (Text-To-Speech) system, we have to know all the possible prosodic rules about Korean language and integrate all of these rules into an algorithm. We can get these rules from linguistic, phonetic knowledge or by analyzi...

Phonetization is a crucial step for oral document processing. In this paper, a new letter-to-phoneme conversion approach is proposed; it is automatic, simple, portable and efficient. It relies on a machine learning technique initially developed for transliteration and translation; the system infers rewriting rules from examples of words with their phonetic representations. This approach is eval...

The improvement of Letter-To-Phoneme (L2P) conversion that can output the phoneme strings corresponding to Out-OfVocabulary (OOV) words, especially in English language, has become one of the most important issues in Text-To-Speech (TTS) research. In this paper, we propose a Two-Stage Neural Network (NN) based approach to solve the problem of conflicting output at a phonemic level. Both Letter a...

An automatic speech segmentation technique is presented that is based on the alignment of a target speech signal with a set of different reference speech signals generated by a specific designed corpus-based speech synthesis system that additionally generates phoneme boundary markers. Each reference signal is then warped to the target speech signal. By synthesizing and warping many different re...

Methods for automated vocal emotion recognition often use acoustic feature vectors that are computed for each frame in an utterance, and global statistics based on these acoustic feature vectors. However, at least two considerations argue for usage of phoneme class specific features for emotion recognition. First, there are well-known effects of phoneme class on some of these features. Second, ...

This paper describes an architecture to convert Sinhala Unicode text into phonemic specification of pronunciation. The study was mainly focused on disambiguating schwa-/\/ and /a/ vowel epenthesis for consonants, which is one of the significant problems found in Sinhala. This problem has been addressed by formulating a set of rules. The proposed set of rules was tested using 30,000 distinct wor...