• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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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.

• 대한음성학회지:말소리
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• 제43호
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• pp.89-99
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• 2002

Recently, researches into ways of improving large vocabulary continuous speech recognition and speech synthesis are being carried out intensively as the field of speech information technology is progressing rapidly. In the field of speech recognition, developments of stochastic methods such as HMM require large amount of speech data for training, and also in the field of speech synthesis, recent practices show that synthesis of better quality can be produced by selecting and connecting only the variable size of speech data from the large amount of speech data. In this paper we design and discuss linguistic contents for speech copora for speech recognition and synthesis to be shared in common.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2443-2446
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• 2003

본 논문에서는 한국전자통신연구원에서 제공된 대어휘 음성DB를 이용하여 HM-Net(Hidden Markov Network) 음성인식 시스템의 성능평가를 수행하였다. 음향모델 작성은 음성인식에서 널리 사용되고 있는 통계적인 모델링 방법인 HMM(Hidden Markov Model)을 개량한 HM-Net을 도입하였다 HM-Net은 PDT-SSS 알고리즘에 의해 문맥방향과 시간방향의 상태분할을 수행하여 생성되는데, 특히 문맥방향 상태분할의 경우 학습 음성데이터에 출현하지 않는 문맥정보를 효과적으로 표현하기 위해 음소결정트리를 채용하고 있으며, 시간방향 상태분할의 경우 학습 음성데이터에서 각 음소별 지속시간 정보를 효과적으로 표현하기 위한 상태분할을 수행한다. 이러한 상태분할을 수행하여 파라미터를 공유하게 되며 최적인 모델 네트워크를 작성하게 된다. 대어휘 음성데이터를 이용하여 음향모델을 작성하고 인식실험을 수행한 결과, 100명의 100단어와 60문장에 대해 평균 97.5％, 96.7％의 인식률을 보였다.

• 대한전자공학회논문지
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• 제24권5호
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• pp.733-739
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• 1987

In this paper, variable threshold detection with weighted pulse code modulation-encoded signals transmitted over Gaussian channels has been investigated. Each bit in the \ulcornerlaw PCM word is weighted according to its significance in the transmitter. It the output falls into the erasure zone, the regenerated sample replaced by interpolation or prediction. To overall system signal to noise ratio for BPSK/PCM speech signals of this technique has been found. When the input signal level was -17 db, the gains in overall signal s/n compared to weighted PCM and variable threshold detection were 5 db and 3 db, respectively. Computer simulation was performed generating signals by computer. The simulation was in resonable agreement with our theoretical prediction.

• 한국통신학회논문지
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• 제37권6C호
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• pp.492-496
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• 2012

본 논문은 잡음이 많이 존재할 경우 특징 보상 기법들의 불완전한 추정 방법으로 인하여 발생할 수 있는 불확실성 정보를 음성 인식의 디코딩에 반영해 줌으로써 좀 더 인식 성능을 향상시킬 수 있는 방법에 대한 연구이다. 기존의 특징 보상 기법들은 현재 시간에서의 깨끗한 특징 파라미터를 추정하는 단일점 추정 기법들이 대부분이다. 하지만 낮은 SNR 환경에서의 잘못된 추정 파라미터들이 음성 인식 엔진의 입력으로 사용될 경우 성능이 저하되기 때문에 추정된 파라미터의 불확실성 정보를 이용하여 디코딩을 해주면 추정 오류를 보완해줄 수 있다. 본 논문에서는 대표적인 Aurora-2 DB를 활용하여 적용된 기법의 성능 향상을 확인한다.

• 음성과학
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• 제15권4호
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• pp.97-105
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• 2008

Nowadays an HMM-based text-to-speech system (HTS) has been very widely studied because it needs less memory and low computation complexity and is suitable for embedded systems in comparison with a corpus-based unit concatenation text-to-speech one. It also has the advantage that voice characteristics and the speaking rate of the synthetic speech can be converted easily by modifying HMM parameters appropriately. We implemented an HMM-based Korean text-to-speech system using a small size Korean speech DB and proposes a method to increase the naturalness of the synthetic speech by controlling duration model parameters in the HMM-based Korean text-to speech system. We performed a paired comparison test to verify that theses techniques are effective. The test result with the preference scores of 73.8% has shown the improvement of the naturalness of the synthetic speech through controlling the duration model parameters.

• 대한음성학회지:말소리
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• 제52호
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• pp.145-160
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• 2004

In this paper, a new noise compensation method based on the eigenvoice framework in feature space is proposed to reduce the mismatch between training and testing environments. The difference between clean and noisy environments is represented by the linear combination of K eigenvectors that represent the variation among environments. In the proposed method, the performance improvement of speech recognition systems is largely affected by how to construct the noisy models and the bias vector set. In this paper, two methods, the one based on MAP adaptation method and the other using stereo DB, are proposed to construct the noisy models. In experiments using Aurora 2 DB, we obtained 44.86% relative improvement with eigen-environment method in comparison with baseline system. Especially, in clean condition training mode, our proposed method yielded 66.74% relative improvement, which is better performance than several methods previously proposed in Aurora project.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.219-222
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• 2003

In this paper, we study the usage of phoneme duration information for rejection garbage sentence. First, we build a phoneme duration modeling in a speech recognition system based on dicicion tree state tying, We assume that phone duration has a Gamma distribution. Next, we build a verification module in which word-level confidence measure is used. Finally, we make a comparative study on phoneme duration with speech DB obtained from the live system. This DB consistes of OOT(out-of-task) and ING(in-grammar) utterences. the usage of phone duration information yields that OOT recognition rate is improved by 46％ and that another 8.4％ error rate is reduced when combined with utterence verification module.

• 음성과학
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• 제9권3호
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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.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.131-134
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• 2003

This paper describes an efficient algorithm to generate compact and complete prompts lists for connected spoken digits database. In building a connected spoken digit recognizer, we have to acquire speech data in various contexts. However, in many speech databases the lists are made by using random generators. We provide an efficient algorithm that can generate compact and complete lists of digits in various contexts. This paper includes the proof of optimality and completeness of the algorithm.