• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.2
• /
• pp.413-418
• /
• 2009

In a speech coding system using excitation source of voiced and unvoiced, it would be involved a distortion of speech qualify in case coexist with a voiced and an unvoiced consonants in a frame. So, We proposed TS(Transition Segment) including unvoiced consonant searching and extraction method in order to uncoexistent with a voiced and unvoiced consonants in a frame. This research present a new method of TS approximate-synthesis by using Least Mean Square and frequency band division. As a result, this method obtain a high qualify approximation-synthesis waveforms within TS by using frequency information of 0.547kHz below and 2.813kHz above. The important thing is that the maximum error signal can be made with low distortion approximation-synthesis waveform within TS. This method has the capability of being applied to a new speech coding of Voiced/Silence/TS, speech analysis and speech synthesis.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.1
• /
• pp.61-68
• /
• 2015

Noise reduction is necessary to compensate for the degradation of recognition performance by various types of noises. Among many noise reduction techniques using microphone array, generalized sidelobe canceller (GSC) has been widely applied to reduce nonstationary noises. The performance of GSC is directly affected by its adaptation mode controller (AMC). That is, accurate target speech detection is essential to guarantee the sufficient noise reduction in pure noise intervals and the less distortion in target speech intervals. Thus, this paper proposes an improved AMC design technique in which the power ratio of the output of fixed beamforming to that of blocking matrix is calculated frequency bandwise and probabilistically modeled by mixture Gaussians for each class. Experimental results show that the proposed algorithm outperforms conventional AMCs in receiver operating curves (ROC) and output SNRs.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.6
• /
• pp.53-61
• /
• 2000

In the speech recognition under the noisy environments, reducing the mismatch introduced between training and testing environments is an important issue. Spectral subtraction is widely used technique because of its simplicity and relatively good performance in noisy environments. In this paper, we introduce histogram method as a reliable noise estimation approach for spectral subtraction. This method has advantages over the conventional noise estimation methods in that it does not need to detect non-speech intervals and it can estimate the noise spectra even in time-varying noise environments. Even though spectral subtraction is performed using a reliable average noise spectrum by the histogram method, considerable amount of residual noise remains due to the variations of instantaneous noise spectrum about mean. To overcome this limitation, we propose a new over-estimation technique based on distribution characteristics of histogram used for noise estimation. Since the proposed technique decides the degree of over-estimation adaptively according to the measured noise distribution, it has advantages to be few the influence of the SNR variation on the noise levels. According to speaker-independent isolated word recognition experiments in car noise environment under various SNR conditions, the proposed histogram-based over-estimation technique outperforms the conventional over-estimation technique.

• Phonetics and Speech Sciences
• /
• v.6 no.2
• /
• pp.21-28
• /
• 2014

We propose a novel scheme for digital audio authentication of given audio files which are edited by inserting small audio segments from different environmental sources. The purpose of this research is to detect inserted sections from given audio files. We expect that the proposed method will assist human investigators by notifying suspected audio section which considered to be recorded or transmitted on different environments. GMM-UBM and GSV-SVM are applied for modeling the dominant environment of a given audio file. Four kinds of likelihood ratio based scores and SVM score are used to measure the likelihood for a dominant environment model. We also use an ensemble score which is a combination of the aforementioned five kinds of scores. In the experimental results, the proposed method shows the lowest average equal error rate when we use the ensemble score. Even when dominant environments were unknown, the proposed method gives a similar accuracy.

• Journal of Veterinary Clinics
• /
• v.18 no.4
• /
• pp.329-333
• /
• 2001

Evaluation on the diagnostic performances of urease test and polymerase chain reaction (PCR) for detection of Helicobacter species infection in dogs has rarely been performed in research with site-specific situations, although assessing diagnostic tests is an essential part prior to its practical use in a variety of clinical settings. The clinical value of a diagnostic test may be misjudged and comparisons between different tests may yield misleading conclusions when high within-patient correlations are present. We applied a conceptually simple statistical approach to estimate the sensitivity and specificity of urease test and PCR for detection of Helicobacter species infection in dogs. This approach assumes that responses from three different sampling sites within an animal are correlated where unit for statistical analysis is the site rather than the animal. The sensitivity and specificity of urease test was 0.74% (95% confidence interval, 0.64-0.84) and 0.87 (95% CI, 0.67-1.00), respectively. For PCR, the sensitivity was 0.95(95% CI, 0.89-1.00) and specificity 0.90 (95% CI, 0.70-1.00). Two tests were almost equally specific. Urease test, however, has a lower diagnostic accuracy and thus should only be used after careful validation in terms of sensitivity.