in this paper, the efficiency of persian speech phonemes from the point of view of efficiency in speaker recognition has been studied, and then with due attention to efficiencies, the ranking of phonemes has been done. for estimating the efficiencies of phonemes, we have introduced one criterion that has been defined in the form of phonemes “inter speaker distance” to “intra speaker distance” r...

Phoneme classification performance is a critical factor for the successful implementation of speech recognition system. A mispronunciation Arabic short vowels or long can change meaning complete sentence. However, correctly distinguishing phonemes with in Quranic recitation (the Holy book Muslims) still challenging problem even state-of-the-art methods, where duration considered one important f...

Construction of a recognizer in a new target language usually involves collection of a comprehensive database in that language as well as manual annotation and model training. For rapid development of new language recognizer, we propose (1) substituting target language phoneme models by source language phoneme models trained previously; and (2) adapting target language phoneme models from sourc...

Both dictionary-based and rule-based methods on grapheme-to-phoneme conversion have their own advantages and limitations. For example, a large sized phonetic dictionary and complex morphophonemic rules are required for the dictionary-based method and the LTS(letter to sound) rule-based method itself cannot model the complete morphophonemic constraints. This paper describes a grapheme-to-phoneme...

This paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and CCV conversion rules. The method consists of mainly four modules including morpheme normalization, phrase-break detection , morpheme to phoneme conversion and phoneme connectivity check. The morpheme normalization is to replace non-Korean symbols into standard Korean graphemes. The phrase-break detector ...

This paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and CCV conversion rules. The method consists of mainly four modules including morpheme normalization, phrase-break detection, morpheme to phoneme conversion and phoneme connectivity check. The morpheme normalization is to replace non-Korean symbols into standard Korean graphemes. The phrase-break detector a...

This paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and CCV conversion rules. The method consists of mainly four modules including morpheme normalization, phrase-break detection, morpheme to phoneme conversion and phoneme connectivity check. The morpheme normalization is to replace non-Korean symbols into standard Korean graphemes. The phrase-break detector a...

BACKGROUND Current cognitive models propose that multiple processes are involved in reading and writing. OBJECTIVE Our goal was to use linguistic analyses to clarify the cognitive dysfunction behind two classic alexic syndromes. METHODS We report four experiments on two patients, one with alexia without agraphia following occipitotemporal lesions, and one with alexia with agraphia from a le...

This paper describes a grapheme-to-phoneme conversion method using phoneme con-nectivity and CCV conversion rules with probabilistic phrase break detection. The method consists of mainly four modules including phrase-break detection, morpheme normalization, morpheme to phoneme conversion and phoneme connectivity check. In the experiments with a test corpus of 210 sentences, we achieved 85% of p...