• MALSORI
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• no.46
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• pp.145-157
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• 2003

In this paper, we'd like to briefly introduce Korean common speech database, which project has been started to construct a large scaled speech database since 2002. The project aims at supporting the R&D environment of the speech technology for industries. It encourages domestic speech industries and activates speech technology domestic market. In the first year, the resulting common speech database consists of 25 kinds of databases considering various recording conditions such as telephone, PC, VoIP etc. The speech database will be widely used for speech recognition, speech synthesis, and speaker identification. On the other hand, although the database was originally corrected by manual, still it retains unknown errors and human errors. So, in order to minimize the errors in the database, we tried to find the errors based on the recognition errors and classify several kinds of errors. To be more effective than typical recognition technique, we will develop the automatic error detection method. In the future, we will try to construct new databases reflecting the needs of companies and universities.

• MALSORI
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• no.47
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• pp.109-120
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• 2003

This paper presents about the activities of speech database standardization in ETRI. Recently, with the support of government, ETRI and SiTEC have been gathering the large speech corpus for the domestic speech related companies. First, due to the lack of sharing the knowledge of speech database specification, the distributed speech database has a different format. Hence it seems to be needed to have the same format as soon as possible. ETRI and SiTEC are trying to find the better representation format of speech database. Second, we introduce a new description method of the annotation information of speech database. As one of the structured description method, XML based description will be applied to represent the metadata of the speech database. It will be continuously revised through the speech technology standard forum during this year.

• Speech Sciences
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• v.9 no.3
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• pp.61-73
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• 2002

We collect the Korean Database which can be trained for the speech recognition engine in an automotive environment. We describe the overall trends of the Korean database collections in this paper and suggest a database collection method for the speech recognition system of the car-kit and explain several conditions in collecting the database in the automotive environments. Finally, we expain an effective method of the Korean database collection in the automobile and the results of the database colletions, and the devised softwares used for the collection of the database.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.61-64
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• 2003

In this paper, we introduce a new description method of annotation information of speech database. As one of structured description methods, XML based description which has been standardized by W3C will be applied to represent metadata of speech database. It will be continuously revised through the speech technology standard forum during this year

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.103-110
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• 2005

Speech Database is one of the most important part of Text-to-speech(TTS) system Especially, the embedded TTS system needs more small size of database than that of the server TTS system So, the compression and statistical reduction or database is a very important factor in the embedded TTS system But this compression and statistical reduction of database always rise a loss of quality of the synthesised speech. In this paper, we propose a method of constructing database for high quality embedded TTS system and verify the quality of synthesised speech with MOS(Mean Opinion Score) test.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.52-59
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• 2012

Children develop their language skill rapidly between age 3 and 5. To meet the child's language development through a variety of experiences, it is necessary to develop age-appropriate contents. So it needs to develop various contents using speech interface for children, but there is no speech database of korean children. In this paper, we develop speech database of 3 to 5 years old children in korean. For collecting accurate children's speech, child education experts examine in the speech database development process. The words for database are selected from MCDI-K in two stage and children speak a word three times. Such collected speech are tokenized by child and word and stored in database. This speech database will be transferred through web and, hopefully, be the foundation of development of children-oriented contents.

• 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.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.23-26
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• 2003

This paper presents common speech database collection for telecommunication applications. During 3 year project, we will construct very large scale speech and text databases for speech recognition, speech synthesis, and speaker identification. The common speech database has been considered various communication environments, distribution of speakers' sex, distribution of speakers' age, and distribution of speakers' region. It consists of Korean continuous digit, isolated words, and sentences which reflects Korean phonetic coverage. In addition, it consists of various pronunciation style such as read speech, dialogue speech, and semi-spontaneous speech. Thanks to the common speech databases, the duplicated resources of Korean speech industries are prohibited. It encourages domestic speech industries and activate speech technology domestic market.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.33-36
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• 2002

As the telematics service that is the integration of information technology approaches commercialization, the necessity and gravity of speech technology is rapidly growing. The speech technology occupies important position in the telematics service because it informs the starting of service and the retrieved result. This service must provide high accuracy of speech recognition and natural synthesis of human speech in a driving environment and it is especially true for the fee-for-service. For high quality TTS, the speech synthesis technique that makes optimal synthesis database and uses efficiently this database is required. In this paper, we describe the design of phonetically balanced sentences used for speech database, the selection of service-suitable-speaker, the extraction methods of accurate phoneme boundary, and the factors which are taken into consideration in the extraction stage of prosody. Finally we show the real case that has commercially implemented.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.87-92
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• 1998

In general, the synthesis unit database was constructed by recording isolated word. In that case, each boundary of word has typical prosodic pattern like a falling intonation or preboundary lengthening. To get natural synthetic speech using these kinds of database, we must artificially distort original speech. However, that artificial process rather resulted in unnatural, unintelligible synthetic speech due to the excessive prosodic modification on speech signal. To overcome these problems, we gathered thousands of sentences for synthesis database. To make a phone level synthesis unit, we trained speech recognizer with the recorded speech, and then segmented phone boundaries automatically. In addition, we used laryngo graph for the epoch detection. From the automatically generated synthesis database, we chose the best phone and directly concatenated it without any prosody processing. To select the best phone among multiple phone candidates, we used prosodic information such as break strength of word boundaries, phonetic contexts, cepstrum, pitch, energy, and phone duration. From the pilot test, we obtained some positive results.