• Proceedings of the KSPS conference
• /
• 2003.05a
• /
• pp.75-78
• /
• 2003

In this paper, we describe a cross-morpheme pronunciation variation model which is especially useful for constructing morpheme-based pronunciation lexicon for Korean LVCSR. There are a lot of pronunciation variations occurring at morpheme boundaries in continuous speech. Since phonemic context together with morphological category and morpheme boundary information affect Korean pronunciation variations, we have distinguished pronunciation variation rules according to the locations such as within a morpheme, across a morpheme boundary in a compound noun, across a morpheme boundary in an eojeol, and across an eojeol boundary. In 33K-morpheme Korean CSR experiment, an absolute improvement of 1.16％ in WER from the baseline performance of 23.17％ WER is achieved by modeling cross-morpheme pronunciation variations with a context-dependent multiple pronunciation lexicon.

• MALSORI
• /
• no.49
• /
• pp.107-121
• /
• 2004

In this paper, we describe a cross-morpheme pronunciation variation model which is especially useful for constructing morpheme-based pronunciation lexicon to improve the performance of a Korean LVCSR. There are a lot of pronunciation variations occurring at morpheme boundaries in continuous speech. Since phonemic context together with morphological category and morpheme boundary information affect Korean pronunciation variations, we have distinguished phonological rules that can be applied to phonemes in within-morpheme and cross-morpheme. The results of 33K-morpheme Korean CSR experiments show that an absolute reduction of 1.45% in WER from the baseline performance of 18.42% WER was achieved by modeling proposed pronunciation variations with a possible multiple context-dependent pronunciation lexicon.

• Phonetics and Speech Sciences
• /
• v.7 no.3
• /
• pp.139-149
• /
• 2015

This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [ɥi] and [$w{\varepsilon}$]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.

• MALSORI
• /
• v.55
• /
• pp.103-118
• /
• 2005

In this paper, we describe a morpheme-based pronunciation lexicon useful for Korean LVCSR. The phonemic-context-dependent multiple pronunciation lexicon improves the recognition accuracy when cross-morpheme pronunciation variations are distinguished from within-morpheme pronunciation variations. Since adding all possible pronunciation variants to the lexicon increases the lexicon size and confusability between lexical entries, we have developed a lexicon pruning scheme for optimal selection of pronunciation variants to improve the performance of Korean LVCSR. By building a proposed pronunciation lexicon, an absolute reduction of $0.56\%$ in WER from the baseline performance of $27.39\%$ WER is achieved by cross-morpheme pronunciation variations model with a phonemic-context-dependent multiple pronunciation lexicon. On the best performance, an additional reduction of the lexicon size by $5.36\%$ is achieved from the same lexical entries.

• Phonetics and Speech Sciences
• /
• v.10 no.4
• /
• pp.111-119
• /
• 2018

This paper proposes a method to improve speech recognition performance by extracting various pronunciations of the pseudo-morpheme unit from an eojeol unit corpus and generating a new recognition unit considering pronunciation variations. In the proposed method, we first align the pronunciation of the eojeol units and the pseudo-morpheme units, and then expand the pronunciation dictionary by extracting the new pronunciations of the pseudo-morpheme units at the pronunciation of the eojeol units. Then, we propose a new recognition unit that relies on pronunciation by tagging the obtained phoneme symbols according to the pseudo-morpheme units. The proposed units and their extended pronunciations are incorporated into the lexicon and language model of the speech recognizer. Experiments for performance evaluation are performed using the Korean speech recognizer with a trigram language model obtained by a 100 million pseudo-morpheme corpus and an acoustic model trained by a multi-genre broadcast speech data of 445 hours. The proposed method is shown to reduce the word error rate relatively by 13.8% in the news-genre evaluation data and by 4.5% in the total evaluation data.

• Journal of KIISE:Software and Applications
• /
• v.34 no.2
• /
• pp.104-111
• /
• 2007

This paper examines how the performance of an automatic speech recognizer was improved for Korean Point-of-Interest (POI) data by modeling pronunciation variation using structural prosodic information such as prosodic words and syllable length. First, multiple pronunciation variants are generated using prosodic words given that each POI word can be broken down into prosodic words. And the cross-prosodic-word variations were modeled considering the syllable length of word. A total of 81 experiments were conducted using 9 test sets (3 baseline and 6 proposed) on 9 trained sets (3 baseline, 6 proposed). The results show: (i) the performance was improved when the pronunciation lexica were generated using prosodic words; (ii) the best performance was achieved when the maximum number of variants was constrained to 3 based on the syllable length; and (iii) compared to the baseline word error rate (WER) of 4.63%, a maximum of 8.4% in WER reduction was achieved when both prosodic words and syllable length were considered.

• International Journal of Advanced Culture Technology
• /
• v.8 no.3
• /
• pp.316-324
• /
• 2020

It has experienced how difficult People with foreign language learning, it is to pronounce a new language different from the native language. The goal of various foreigners who want to learn Korean is to speak Korean as well as their native language to communicate smoothly. However, each native language's vocal habits also appear in Korean pronunciation, which prevents accurate information transmission. In this paper, the pronunciation of Chinese learners was compared with that of Korean. For comparison, the fundamental frequency and its variation of the speech signal were examined and the spectrogram was analyzed. The Formant frequencies known as the resonant frequency of the vocal tract were calculated. Based on these characteristics parameters, the classifier of the Supporting Vector Machine was found to classify the pronunciation of Koreans and the pronunciation of Chinese learners. In particular, the linguistic proposition was scientifically proved by examining the Korean pronunciation of /ㄹ/ that the Chinese people were not good at pronouncing.

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

• Phonetics and Speech Sciences
• /
• v.15 no.1
• /
• pp.9-17
• /
• 2023

The purpose of this study is to determine how the Korean diphthong /jo/ shows phonetic variation in various linguistic environments. The pronunciation of /jo/ is discussed, focusing on the relationship between phonetic variation and the distribution range of vowels. The location in a word (monosyllable, word-initial, word-medial, word-final) and word class (content word, function word) were analyzed using the speech of 10 female speakers of the Seoul Corpus. As a result of determining the frequency of appearance of /jo/ in each environment, the pronunciation type and word class were affected by the location in a word. Frequent phonetic reduction was observed in the function word /jo/ in the acoustic analysis. The word class did not change the average phonetic values of /jo/, but changed the distribution of individual tokens. These results indicate that the linguistic environment affects the phonetic distribution of vowels.

• Korean Linguistics
• /
• v.63
• /
• pp.103-132
• /
• 2014

This study compares various speech rates of Korean learners with those of native Korean. Speech data were collected from 34 native Koreans and 33 Korean learners (19 Chinese and 14 Japanese). Each participant recorded a 9 syllabled Korean sentence at three different speech rate types. A total of 603 speech samples were analyzed by speech rate types (normal, slow, and fast), native languages (Korean, Chinese, Japanese), and learners' proficiency levels (beginner, intermediate, and advanced). We found that learners' L1 background plays a role in categorizing different speech rates in the L2 (Korean), and also that the leaners' proficiency correlates with the increase of speaking rate regardless of speech rate categories. More importantly, faster speech rate values found in the advanced level of learners do not necessarily match to the native speakers' speech rate categories. This means that learning speech rate categories can be more complex than we think of proficiency or fluency. That is, speech rate categories may not be acquired automatically during the course of second language learning, and implicit or explicit exposures to various rate types are necessary for second language learners to acquire a high level of communicative skills including speech rate variation. This paper discusses several pedagogical implications in terms of teaching pronunciation to second language learners.