Abstract A phoneme is perceptually the smallest distinct sound unit distinguished among words in a particular language. Every language has its own set of phonemes, and all are ordered sequences phonemes. Therefore, recognition essential to automatic speech (ASR) systems. Phonemes can be classified together using single machine learning (ML) model through direct classification (also known as bas...

The focus of this paper is to formulate an approach to merging phonemes across languages and to evaluate the resulting crosslanguage merged speech units on the basis of the traditional acousticphonetic descriptions of the phonemes. The methodology is based on the belief that some phonemes across a set of languages may be similar enough to be equated, contrasting traditional phonology which trea...

Speech recognition consists of converting input sound into a sequence phonemes, then finding text for the using language models. Therefore, phoneme classification performance is critical factor successful implementation speech system. However, correctly distinguishing phonemes with similar characteristics still challenging problem even state-of-the-art methods, and errors are hard to be recover...

• These sounds are grouped into closely related families of sounds; each such family acts as a single unit from a phonemic point of view. We call these families “phonemes,” and in some respects we are more aware of these phonemes than we are of the very sounds themselves. A word can be viewed as a sequence of sounds, or as a sequence of phonemes. Neither view is more correct; they are at differ...

Phonemic restoration is the perceptual synthesis of phonemes when masked by appropriate replacement sounds by utilizing linguistic context. Current models attempting to accomplish acoustic restoration of phonemes, however, use only temporal continuity and produce poor restoration of unvoiced phonemes, and are also limited in their ability to restore voiced phonemes. We present a schema-based mo...