• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.39-50
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• 2005

Speech DB is basically required factor when we are study for phonetics, speech recognition and speech synthesis and so on. The quantity and quality of speech DB decide the efficiency of system that we develop. therefore. speech DB has an extremely important factor, Recently, development of the various telephone service technique such as voice portal. it is actual condition where the necessity of collection of telephone speech DB. The existing IVR application telephone speech DB collection system used C/C++ language or the exclusive development tool. Thus it is the actual condition where the recycle of each application service for resources is difficult and have a problem of many labors and time necessity. But. VoiceXML is a language having tag form ipredicated in XML. which has easy and simple grammar system. Therefore, if we make a few efforts we could draw up easily. it has a merit reducing labors and time, Also, VoiceXML has many advantages of various telephone speech DB gathering because of changing contents of DB. In this paper, we introduce telephone speech DB gathering system which is the mast important factor for development of speech information processing technique.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.91-98
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• 2010

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. Because the improvements in the natualness, personality, speaking style, emotions of synthetic speech need the increase of the size of speech DB, it is necessary to prune the redundant speech segments in a large speech segment DB. In this paper, we propose a new method to construct a segmental speech DB for the Korean TTS system based on a clustering algorithm to downsize the segmental speech DB. For the performance test, the synthetic speech was generated using the Korean TTS system which consists of the language processing module, prosody processing module, segment selection module, speech concatenation module, and segmental speech DB. And MOS test was executed with the a set of synthetic speech generated with 4 different segmental speech DBs. We constructed 4 different segmental speech DB by combining CM1(or CM2) tree clustering method and full DB (or reduced DB). Experimental results show that the proposed method can reduce the size of speech DB by 23% and get high MOS in the perception test. Therefore the proposed method can be applied to make a small sized TTS.

• MALSORI
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• no.47
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• pp.51-72
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• 2003

The purpose of this paper is to design Speech Database for Korean pronunciation education. For this purpose, I investigated types of speech errors of Korean-learners, made texts for recording, which involves all types of speech errors, and showed how to gather speech data and how to tag their informations. It's natural that speech data should include Korean-learners' speech and Korean people's speech, because Speech DB that I try to develop is for teaching Korean pronunciation to foreigners. So this DB should have informations about speakers and phonetic informations, which are about phonetic value of segments and intonation of sentences. The intonation of sentence varies with the type of sentence, the structure of prosodic units, the length of a prosodic unit and so on. For this reason, Speech DB must involve tags about these informations.

• Phonetics and Speech Sciences
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• v.9 no.2
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• pp.9-22
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• 2017

The purpose of this paper is to report the whole process of developing Korean Standard Speech Database (KSS DB). This project is supported by SPO (Supreme Prosecutors' Office) research grant for three years from 2014 to 2016. KSS DB is designed to provide speech data for acoustic-phonetic and phonological studies and speaker recognition system. For the samples to represent the spoken Korean, sociolinguistic factors, such as region (9 regional dialects), age (5 age groups over 20) and gender (male and female) were considered. The goal of the project is to collect over 3,000 male and female speakers of nine regional dialects and five age groups employing direct and indirect methods. Speech samples of 3,191 speakers (2,829 speakers and 362 speakers using direct and indirect methods, respectively) are collected and databased. KSS DB designs to collect read and spontaneous speech samples from each speaker carrying out 5 speech tasks: three (pseudo-)spontaneous speech tasks (producing prolonged simple vowels, 28 blanked sentences and spontaneous talk) and two read speech tasks (reading 55 phonetically and phonologically rich sentences and reading three short passages). KSS DB includes a 16-bit, 44.1kHz speech waveform file and a orthographic file for each speech task.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.21-24
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• 2002

본 논문은 ETRI 음성정보연구센터에서 추진하고 있는 공통음성 DB 구축에 관하여 기술한다. 총 3 년(2001 11-2004. 10) 동안 음성인식, 음성합성, 화자인식 등 다양한 용도의 음성 DB 를 수집할 예정이며, 1년차인 2002 년에는 총 14 종의 음성 DB 를 수집할 계획이다. 공통 음성 DB 는 다양한 통신망(마이크, 헤드셋, VoIP, 유무선 전화망), 지역, 성별, 발성환경(사무실, 지하철, 도로 등)을 고려하여 설계하였으며, 발성대상은 숫자, 단어, 문장이고, 발성방법은 자유발화, 대화체, 낭독체 등 다양한 스타일의 음성 DB 로 구성되어 있다. 이에 본 논문에서는 총 14 종에 해당하는 공통음성 DB 의 구축내역과 구축방안 및 DB 구축 일정에 관해 기술하고자 한다.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.703-710
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• 2003

Because of their human-like synthesized speech quality, recently Corpus-Based Text-To-Speech(CB-TTS) have been actively studied worldwide. However, due to their large size speech database (DB), their application is very restricted. In this paper we propose and evaluate three DB reduction algorithms to which are designed to solve the above drawback. The first method is based on a K-means clustering approach, which selects k-representatives among multiple instances. The second method is keeping only those unit instances that are selected during synthesis, using a domain-restricted text as input to the synthesizer. The third method is a kind of hybrid approach of the above two methods and is using a large text as input in the system. After synthesizing the given sentences, the used unit instances and their occurrence information is extracted. As next step a modified K-means clustering is applied, which takes into account also the occurrence information of the selected unit instances, Finally we compare three pruning methods by evaluating the synthesized speech quality for the similar DB reduction rate, Based on perceptual listening tests, we concluded that the last method shows the best performance among three algorithms. More than this, the results show that the last method is able to reduce DB size without speech quality looses.

• MALSORI
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• v.55
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• pp.143-158
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• 2005

The adequate compression algorithm is essential to achieve high quality embedded TTS system. in this paper, we Propose waveform interpolation coder for TTS corpus compression after many speech coder investigation. Unlike speech coders in communication system, compression rate and anality are more important factors in TTS DB compression than other performance criteria. Thus we select waveform interpolation algorithm because it provides good speech quality under high compression rate at the cost of complexity. The implemented coder has bit rate 6kbps with quality degradation 0.47. The performance indicates that the waveform interpolation is adequate for TTS DB compression with some further study.

• 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.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.29-32
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• 2002

본 논문에서는 ETRI 의 음성정보연구센터에서 추진하고 있는 공통 음성 DB 구축을 위한 발성목록의 설계 방법 및 그 내용에 대해 기술한다. 이 공통 음성 DB는 국내의 학계와 연구기관, 산업체에 배포하여 음성기술개발에 활용될 수 있도록 하려는 목적으로 구축되는 대규모의 DB인 만큼, 다양한 활용 분야를 고려하여 설계되었다. 따라서 내용적으로 중립성을 유지하면서도 효율성과 기능성을 고려하여 설계한 것이 이번 발성목록 설계의 특징이라고 할 수 있다. 이번 발성목록은 크게 음성 인식용 DB 와 낭독체 합성용 DB, 대화체 합성용 DB, 그리고 화자 인식용 DB 분야로 나뉘어진다. 이 논문에서는 각 DB 종류별로 발성 목록의 내용과 작성 방법, 그리고 이들을 작성함에 있어서 고려된 사항 등을 기술한다.

• MALSORI
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• no.48
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• pp.141-153
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• 2003

Researches into robust recognition in noise environments, especially in car environments, are being carried out actively in speech community. In this paper we will report on three types of corpora that SiTEC (Speech Information TEchnology & industry promotion Center) has created for research into speech recognition in car noise environments. The first is the recordings of 900 Korean native speakers, distributed according to gender, age, and region, who uttered application words in car environments. The second is the collections of mixed noise in 3 car types by model while setting up various noise patterns which can be obtained with the car engine on or off, at different driving speed, and in different road conditions with windows open or closed. The third is the recordings of simulated speech by HATS (Head and Torso Simulator) in car environments with the internal and external noise factors added. These three types of recordings were all made through synchronized 8 channel microphones that are fixed in a car. The creation and applications of these corpora will be reported on in detail.