• Speech Sciences
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• v.10 no.2
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• pp.7-25
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• 2003

Predicting the right prosodic elements is a key factor in improving the quality of synthesized speech. Prosodic elements include break, pitch, duration and loudness. Pitch, which is realized by Fundamental Frequency (F0), is the most important element relating to the quality of the synthesized speech. However, the previous method for predicting the F0 appears to reveal some problems. If voiced and unvoiced sounds are not correctly classified, it results in wrong prediction of pitch, wrong unit of triphone in synthesizing the voiced and unvoiced sounds, and the sound of click or vibration. This kind of feature is usual in the case of the transformation from the voiced sound to the unvoiced sound or from the unvoiced sound to the voiced sound. Such problem is not resolved by the method of grammar, and it much influences the synthesized sound. Therefore, to steadily acquire the correct value of pitch, in this paper we propose a new model for predicting and classifying the voiced and unvoiced sounds using the CART tool.

• Speech Sciences
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• v.12 no.1
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• pp.55-63
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• 2005

This paper introduces a 'Hanmal' Korean language diphone database for speech synthesis, which has been publicly available since 1999 in the MBROLA web site and never been properly published in a journal. The diphone database is compatible with the MBROLA programme of high-quality multilingual speech synthesis systems. The usefulness of the diphone database is introduced in the paper. The paper also describes the phonetic and phonological structure of the database, showing the process of creating a text corpus. A machine-readable Korean SAMPA convention for the control data input to the MBROLA application is also suggested. Diphone concatenation and prosody manipulation are performed using the MBR-PSOLA algorithm. A set of segment duration models can be applied to the diphone synthesis of Korean.

• Phonetics and Speech Sciences
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• v.8 no.1
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• pp.45-51
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• 2016

This study examined the deletion of onset consonant in the word-internal structure in spontaneous Seoul Korean speech. It used the dataset of speakers in their 20s extracted from the Korean Corpus of Spontaneous Speech (Yun et al., 2015). The proportion of deletion of word-internal onset consonants was analyzed using the linear mixed-effects regression model. The factors that promoted the deletion of onsets were primarily the types of consonants and their phonetic contexts. The results showed that onset deletion was more likely to occur for a lenis velar stop [k] than the other consonants, and in the phonetic contexts, when the preceding vowel was a low central vowel [a]. Moreover, some speakers tended to more frequently delete onset consonants (e.g., [k] and [n]) than other speakers, which reflected individual differences. This study implies that word-internal onsets undergo a process of gradient reduction within individuals' articulatory strategies.

• Speech Sciences
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• v.8 no.1
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• pp.77-91
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• 2001

This paper investigates the timing of Korean spoken in a news-reading speech style in order to improve the naturalness of durations used in Korean speech synthesis. Each segment in a corpus of 671 read sentences was annotated with 69 segmental and prosodic features so that the measured duration could be correlated with the context in which it occurred. A CART model based on the features showed a correlation coefficient of 0.79 with an RMSE (root mean squared prediction error) of 23 ms between actual and predicted durations in reserved test data. These results are comparable with recent published results in Korean and similar to results found in other languages. An analysis of the classification tree shows that phrasal structure has the greatest effect on the segment duration, followed by syllable structure and the manner features of surrounding segments. The place features of surrounding segments only have small effects. The model has application in Korean speech synthesis systems.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4E
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• pp.26-30
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• 1999

This paper introduces a prosodic phrasing method in Korean to improve the naturalness of speech synthesis, especially in text-to-speech conversion. In prosodic phrasing, it is necessary to understand the structure of a sentence through a language processing procedure, such as part-of-speech (POS) tagging and parsing, since syntactic structure correlates better with the prosodic structure of speech than with other factors. In this paper, the prosodic phrasing procedure is treated from two perspectives: dependency parsing and prosodic phrasing using dependency relations. This is appropriate for Ural-Altaic, since a prosodic boundary in speech usually concurs with a governor of dependency relation. From experimental results, using the proposed method achieved 12% improvement in prosody boundary prediction accuracy with a speech corpus consisting 300 sentences uttered by 3 speakers.

• English Language & Literature Teaching
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• v.16 no.4
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• pp.91-106
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• 2010

This study examines the use of hedges in cross-cultural communication between EFL learners in an e-learning environment. The study analyzes the use of hedges in a corpus of an interactive web with a bulletin board system through which college students of English at Japanese and Korean universities interacted with each other discussing the topics of local and global issues. It compares the use of hedges in the students' corpus to that of a native English speakers' corpus. The result shows that EFL learners tend to use relatively smaller number of hedges than the native speakers in terms of the frequencies of the total tokens. It further reveals that the learners' overuse of a single versatile high-frequency hedging item, I think, results in relative underuse of other hedging devices. This indicates that due to their small repertoire of hedges, EFL learners' overuse of a limited number of hedging items may cause their speech or writing to become less competent. Based on the result and interviews with the learners, the study also argues that hedging should be understood in its social contexts and should not be understood just as a lack of conviction or a mark of low proficiency. Suggestions were made for using computer corpora in understanding EFL learners' language difficulties and helping them develop communicative and pragmatic competence.

• Proceedings of the IEEK Conference
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• summer
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• pp.103-109
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• 2004

In NLP (Natural Language Processing) tasks, the highest difficulty which computers had to face with, is the built-in ambiguity of Natural Languages. To disambiguate it, formerly, they based on human-devised rules. Building such a complete rule-set is time-consuming and labor-intensive task whilst it doesn't cover all the cases. Besides, when the scale of system increases, it is very difficult to control that rule-set. So, recently, many NLP tasks have changed from rule-based approaches into corpus-based approaches with large annotated corpora. Corpus-based NLP tasks for such popular languages as English, French, etc. have been well studied with satisfactory achievements. In contrast, corpus-based NLP tasks for Vietnamese are at a deadlock due to absence of annotated training data. Furthermore, hand-annotation of even reasonably well-determined features such as part-of-speech (POS) tags has proved to be labor intensive and costly. In this paper, we present our building an annotated English-Vietnamese parallel aligned corpus named EVC to train for Vietnamese-related NLP tasks such as Word Segmentation, POS-tagger, Word Order transfer, Word Sense Disambiguation, English-to-Vietnamese Machine Translation, etc.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• Smart Media Journal
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• v.11 no.5
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• pp.17-25
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• 2022

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

• Phonetics and Speech Sciences
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• v.8 no.4
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• pp.39-47
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• 2016

While acoustic studies in the past decade documented a raised /o/ by showing their lowered first formants (F1) almost overlapped with those of high back vowel /u/, no consensus has been made in terms of how this /o/-raising affects the vowels as a system in Seoul Korean. The current study aimed to investigate the age- and gender-related differences of the relative distance among the vowels to better understand the influence of this on-going sound change on the vowel system. We measured the static and dynamic spectral characteristics (F1 and F2) of the seven Korean monophthong vowels /e a ʌ o u ɨ i/ in the spontaneous speech of Seoul Corpus, and depicted the patterns of 30 individual speakers (10 speakers in each group of teens, 20s and 40s) as a function of age and gender. The static spectral examination showed low F1 values of /o/ in the spontaneous speech corpus confirming the vowel /o/ raising, and also revealed greater F2 values of /u, ɨ/ suggesting their anterior articulations. The tendencies were stronger when the speakers were younger and female. The spectral trajectories further showed that the F1 and F2 between /o/ and /u/ were differentiated throughout the vowel mid-point although the trajectories gradually merged near the vowel mid point in the older male speakers' productions. The acoustic evidence of contrast among /o, u, ɨ/ supports that the raised /o/ is not indicative of a merger with /u/ but rather implying a chain-like vowel shift in the Seoul Korean.