• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.49-55
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• 2018

This paper aims to describe a knowledge-based pronunciation generation system for French. It has been reported that a rule-based pronunciation generation system outperforms most of the data-driven ones for French; however, only a few related studies are available due to existing language barriers. We provide basic information about the French language from the point of view of the relationship between orthography and pronunciation, and then describe our knowledge-based pronunciation generation system, which consists of morphological analysis, Part-of-Speech (POS) tagging, grapheme-to-phoneme generation, and phone-to-phone generation. The evaluation results show that the word error rate of POS tagging, based on a sample of 1,000 sentences, is 10.70% and that of phoneme generation, using 130,883 entries, is 2.70%. This study is expected to contribute to the development and evaluation of speech synthesis or speech recognition systems for French.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.241-248
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• 2007

In this paper, we propose a Transformation-Based Learning (TBL) method on generating the Korean standard pronunciation. Previous studies on the phonological processing have been focused on the phonological rule applications and the finite state automata (Johnson 1984; Kaplan and Kay 1994; Koskenniemi 1983; Bird 1995). In case of Korean computational phonology, some former researches have approached the phonological rule based pronunciation generation system (Lee et al. 2005; Lee 1998). This study suggests a corpus-based and data-oriented rule learning method on generating Korean standard pronunciation. In order to substituting rule-based generation with corpus-based one, an aligned corpus between an input and its pronunciation counterpart has been devised. We conducted an experiment on generating the standard pronunciation with the TBL algorithm, based on this aligned corpus.

• MALSORI
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• no.48
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• pp.57-67
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• 2003

This paper presents a systematic description of exceptional pronunciations for automatic Korean pronunciation generation. An automatic pronunciation generator in Korean is an essential part of a Korean speech recognition system and a TTS (Text-To-Speech) system. It is composed of a set of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words that have exceptional pronunciations, based on the characteristics of the words of exceptional pronunciation through phonological research and the systematic analysis of the entries of Korean dictionaries. Thus, the method contributes to improve performance of automatic pronunciation generator in Korean as well as the performance of speech recognition system and TTS system in Korean.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.41-44
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• 2002

This paper is related to the enhancement of speech recognition rate using enhanced pronunciation dictionary. Modern large vocabulary, continuous speech recognition systems have pronunciation dictionaries. A pronunciation dictionary provides pronunciation information for each word in the vocabulary in phonemic units, which are modeled in detail by the acoustic models. But in most speech recognition system based on Hidden Markov Model, actual pronunciation variations are disregarded. Without the pronunciation variations in the speech recognition system, the phonetic transcriptions in the dictionary do not match the actual occurrences in the database. In this paper, we proposed the unvoiced rule of semivowel in allophone rules to pronunciation dictionary. Experimental results on speech recognition system give higher performance than existing pronunciation dictionaries.

• MALSORI
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• no.49
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• pp.1-30
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• 2004

Although Standard Korean is based on Seoul Korean, the phonetic realization of syllable codas in Seoul Korean has not been satisfactorily investigated. This paper aims to study how Seoul speakers pronounce syllable codas in certain phonetic contexts and what pronunciation they prefer among variants. It is noted that the realization of a syllable coda is different word by word and generation by generation. It is also noted that the syllable coda of a word is realized differently depending on the following vowel. And we discussed how the Principles of Standard Korean Pronunciation should be revised in the future, based on the results of this study.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.151-162
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• 2009

This paper aims to investigate how tensification preference has changed over time and discuss how appropriately tensification preference is reflected in Principles of Standard Pronunciation and Standard Korean Language Dictionary. For this research, a questionnaire survey of tensification preference was conducted. 173 test words were used and 156 native Seoul speakers participated in this survey. The results have shown that tensification preference has gradually increased from older to younger generations. In addition, Principles of Standard Pronunciation and Standard Korean Language Dictionary do not reflect real pronunciation appropriately. Therefore, some ways of incorporating the actual pronunciation of Seoul speakers in the Principles of Standard Pronunciation and the Standard Korean Language Dictionary are suggested.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.248-252
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• 2004

Cultural, social, economic and other various environmental factors affect our language and different words and terminology are used and coined for different contexts, resulting in quantitative change of vocabulary. This paper presents an automatic pronunciation generator using selection procedure for exceptional pronunciation words from added text corpus, which reflects this dynamic nature of language. For our experiment, we used the text corpus released by ETRI for speech recognition. consisting or 53,750 sentences (740.497 Eojols), and obtained a 100% performance level of the proposed automatic pronunciation generator.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.35-43
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• 2001

Many speech recognition systems have used pronunciation lexicon with possible multiple phonetic transcriptions for each word. The pronunciation lexicon is of often manually created. This process requires a lot of time and efforts, and furthermore, it is very difficult to maintain consistency of lexicon. To handle these problems, we present a model based on morphophon-ological analysis for automatically generating Korean pronunciation variants. By analyzing phonological variations frequently found in spoken Korean, we have derived about 700 phonemic contexts that would trigger the multilevel application of the corresponding phonological process, which consists of phonemic and allophonic rules. In generating pronunciation variants, morphological analysis is preceded to handle variations of phonological words. According to the morphological category, a set of tables reflecting phonemic context is looked up to generate pronunciation variants. Our experiments show that the proposed model produces mostly correct pronunciation variants of phonological words. Then we estimated how useful the pronunciation lexicon and training phonetic transcription using this proposed systems.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.81-85
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• 2002

We present a statistical analysis of Korean phonological variations using automatic generation of phonetic transcription. We have constructed the automatic generation system of Korean pronunciation variants by applying rules modeling obligatory and optional phonemic changes and allophonic changes. These rules are derived from knowledge-based morphophonological analysis and government standard pronunciation rules. This system is optimized for continuous speech recognition by generating phonetic transcriptions for training and constructing a pronunciation dictionary for recognition. In this paper, we describe Korean phonological variations by analyzing the statistics of phonemic change rule applications for the 60,000 sentences in the Samsung PBS(Phonetic Balanced Sentence) Speech DB. Our results show that the most frequently happening obligatory phonemic variations are in the order of liaison, tensification, aspirationalization, and nasalization of obstruent, and that the most frequently happening optional phonemic variations are in the order of initial consonant h-deletion, insertion of final consonant with the same place of articulation as the next consonants, and deletion of final consonant with the same place of articulation as the next consonants. These statistics can be used for improving the performance of speech recognition systems.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.59-64
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• 2017

There are three sorts of voices of female vocalists: soprano, mezzo-soprano, and contralto according to the transliteration. Among them, the soprano has the highest vocal range. Since the voice is generated through the human vocal tract based on the voice generation model, it is greatly influenced by the vocal tract. The structure of vocal organs differs from person to person, and the formants characteristic of vocalization differ accordingly. The formant characteristic refers to a characteristic in which a specific frequency band appears distinctly due to resonance occurring in each vocal tract in the vocal process. Formant characteristics include personality that occurs in the throat, jaw, lips, and teeth, as well as phonological properties of phonemes. The first formant is the throat, the second formant is the jaw, the third formant and the fourth formant are caused by the resonance phenomenon in the lips and the teeth. Among them, pronunciation is influenced not only by phonological information but also by jaws, lips and teeth. When the mouth is small or the jaw is stiff when pronouncing, pronunciation becomes unclear. Therefore, the higher the accuracy of the pronunciation characteristics, the more clearly the formant characteristics appear in the grammar spectrum. However, many soprano singers can not open their mouths because their jaws, lips, teeth, and facial muscles are rigid to maintain high tones when singing, which makes the pronunciation unclear and thus the formant characteristics become unclear. In this paper, in order to confirm the accuracy of the pronunciation characteristics of soprano singers, the experimental group was selected as the soprano singers A, B, C, D, E of Korea and analyzed the grammar spectrum and conducted the MOS test for pronunciation recognition. As a result, soprano singer B showed a clear recognition from F1 to F5 and MOS test result showed the highest recognition rate with 4.6 points. Soprano singers A, C, and D appear from F1 to F3, but it was difficult to find formants above 2kHz. Finally, the soprano singer E had difficulty in finding the formant as a whole, and MOS test showed the lowest recognition rate at 2.1 points. Therefore, we confirmed that the soprano singer B, which exhibits the most distinct formant characteristics in the grammar spectrum, has the best pronunciation accuracy.