• Proceedings of the KSPS conference
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• 2005.11a
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• pp.63-66
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• 2005

For the Large Corpus based TTS the consistency of the speech corpus is very important. It is because the inconsistency of the speech quality in the corpus may result in a distortion at the concatenation point. And because of this inconsistency, large corpus must be tuned repeatedly One of the reasons for the inconsistency of the speech corpus is the different glottal characteristics of the speech sentence in the corpus. In this paper, we adjusted the glottal characteristics of the speech in the corpus to prevent this distortion. And the experimental results are showed.

• Phonetics and Speech Sciences
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• v.6 no.3
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• pp.139-145
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• 2014

The paper describes methods of conducting vowel analysis from a large-scale corpus with the aids of forced alignment and optimal formant ceiling methods. 'Read Style Corpus of Standard Korean' is used for building the forced alignment system and a subset of the corpus for the processing and extraction of features for vowel analysis based on optimal formant ceiling. The results of the vowel analysis are reliable and comparable to the results obtained using traditional analytical methods. The findings indicate that the methods adopted for the analysis can be extended and be used for more fine-grained analysis without time-consuming manual labeling without losing accuracy and reliability.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.103-106
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• 2005

In this paper, we propose a language modeling approach to improve the performance of a large vocabulary continuous speech recognition system. The proposed approach is based on the active learning framework that helps to select a text corpus from a plenty amount of text data required for language modeling. The perplexity is used as a measure for the corpus selection in the active learning. From the recognition experiments on the task of continuous Korean speech, the speech recognition system employing the language model by the proposed language modeling approach reduces the word error rate by about 6.6 % with less computational complexity than that using a language model constructed with randomly selected texts.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.139-150
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• 2015

The data accumulated in this database will be used to develop a speaker identification system. This may also be applied towards, but not limited to, fields of phonetic studies, sociolinguistics, and language pathology. We plan to supplement the large-scale speech corpus next year, in terms of research methodology and content, to better answer the needs of diverse fields. The purpose of this study is to develop a speech corpus for standard Korean speech. For the samples to viably represent the state of spoken Korean, demographic factors were considered to modulate a balanced spread of age, gender, and dialects. Nine separate regional dialects were categorized, and five age groups were established from individuals in their 20s to 60s. A speech-sample collection protocol was developed for the purpose of this study where each speaker performs five tasks: two reading tasks, two semi-spontaneous speech tasks, and one spontaneous speech task. This particular configuration of sample data collection accommodates gathering of rich and well-balanced speech-samples across various speech types, and is expected to improve the utility of the speech corpus developed in this study. Samples from 639 individuals were collected using the protocol. Speech samples were collected also from other sources, for a combined total of samples from 1,012 individuals.

• Phonetics and Speech Sciences
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• v.10 no.2
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• pp.7-14
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• 2018

The paper investigates the acoustic characteristics of English fricatives in the TIMIT corpus, with a special focus on the role of voicing in rendering fricatives in American English. The TIMIT database includes 630 talkers and 2,342 different sentences, and comprises more than five hours of speech. Acoustic analyses are conducted in the domain of spectral and temporal properties by treating gender, voicing, and place of articulation as independent factors. The results of the acoustic analyses revealed that acoustic signals interact in a complex way to signal the gender, place, and voicing of fricatives. Classification experiments using a multiclass support vector machine (SVM) revealed that 78.7% of fricatives are correctly classified. The majority of errors stem from the misclassification of /θ/ as [f] and /ʒ/ as [z]. The average accuracy of gender classification is 78.7%. Most errors result from the classification of female speakers as male speakers. The paper contributes to the understanding of the effects of voicing and gender on fricatives in a large-scale speech corpus.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.209-213
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• 2002

This paper describes the reduction of DB without degradation of speech quality in Corpus-based Speech synthesizer of Korean language. In this paper, it is proposed that the frequency of every unit in reduced DB should reflect the frequency of units in Korean language. So, the target population of every unit is set to be proportional to their frequency in Korean large corpus(780K sentences, 45Mega phonemes). Second, the frequent instances during synthesis should be also maintained in reduced DB. To the last, it is proposed that frequency of every instance should be reflected in clustering criterion and used as criterion for selection of representative instances. The evaluation result with proposed methods reveals better quality than using conventional methods.

• MALSORI
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• no.44
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• pp.145-156
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• 2002

This paper describes the reduction of DB without degradation of speech quality in Corpus-based Speech synthesizer of the Korean language. In this paper, it is proposed that the frequency of every unit in reduced DB reflect the frequency of units in the Korean language. So, the target population of every unit is set to be proportional to its frequency in Korean large corpus (780k sentences, 45Mega phones). Secondly, the frequent instances during synthesis should be also maintained in reduced DB. To the last, it is proposed that frequency of every instance be reflected in clustering criteria and used as another important criterion for selection of representative instances. The evaluation result with proposed methods reveals better quality than that using conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3992-3998
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• 2013

This paper is related to the method of adding a emotional speech corpus to a high-quality large corpus based speech synthesizer, and generating various synthesized speech. We made the emotional speech corpus as a form which can be used in waveform concatenated speech synthesizer, and have implemented the speech synthesizer that can be generated various synthesized speech through the same synthetic unit selection process of normal speech synthesizer. We used a markup language for emotional input text. Emotional speech is generated when the input text is matched as much as the length of intonation phrase in emotional speech corpus, but in the other case normal speech is generated. The BIs(Break Index) of emotional speech is more irregular than normal speech. Therefore, it becomes difficult to use the BIs generated in a synthesizer as it is. In order to solve this problem we applied the Variable Break[3] modeling. We used the Japanese speech synthesizer for experiment. As a result we obtained the natural emotional synthesized speech using the break prediction module for normal speech synthesize.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.123-130
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• 2013

Previous researches on Korean intonation have been mainly focused on $F_0$ target frequencies, $F_0$ slope, and the duration of intonation patterns. This study investigated Korean intonation patterns, both boundary and phrasal tones, in relation to the $F_0$ percentage change between pitch targets. We measured the percentage change between the pitch targets of both boundary and phrasal tones. Additionally, the $F_0$ change between the preceding pitch target and the first pitch target of the boundary tone and the $F_0$ targets of the sequence of two LH phrasal tones ('LH + LH') were also measured. Two phrasal tones, LHLH and HLH, were compared with 'LH + LH' and the 'HLH' in the LHLH pattern respectively. We found that the percentage change between pitch targets in the phrasal tone is fixed to some extent. This helped explain why the slope of the phrasal tone is closely related to the number of syllables and the duration of the phrasal tone as discussed in previous studies. Since we analyzed the intonation patterns with the utterances from a large speech corpus, the results of this paper are expected to be used in building a larger annotated corpus of Korean.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.117-124
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• 2015

This paper investigates the acoustic characteristics of English fricatives in the TIMIT corpus, with a special focus on the role of gender in rendering fricatives in American English. The TIMIT database includes 630 talkers and 2342 different sentences, comprising over five hours of speech. Acoustic analyses are conducted in the domain of spectral and temporal properties by treating gender as an independent factor. The results of acoustic analyses revealed that the most acoustic properties of voiceless sibilants turned out to be different between male and female speakers, but those of voiceless non-sibilants did not show differences. A classification experiment using linear discriminant analysis (LDA) revealed that 85.73% of voiceless fricatives are correctly classified. The sibilants are 88.61% correctly classified, whereas the non-sibilants are only 57.91% correctly classified. The majority of the errors are from the misclassification of /ɵ/ as [f]. The average accuracy of gender classification is 77.67%. Most of the inaccuracy results are from the classification of female speakers in non-sibilants. The results are accounted for by resorting to biological differences as well as macro-social factors. The paper contributes to the understanding of the role of gender in a large-scale speech corpus.