• English Language & Literature Teaching
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• v.13 no.2
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• pp.47-61
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• 2007

The purpose of this paper is to survey the major elements that have changed English from a synthetic language to an analytic one. Therefore, this paper has looked at the differences between synthetic languages and analytic ones. In synthetic languages, the relation of words in a sentence is synthetically determined by means of inflections, while in analytic languages, the functions of words in a sentence are analytically determined by means of word order and function words. Thus, Old English with full inflectional systems shows the synthetic nature. However, in the course of time, Old English inflections came to be lost by phonetic changes and operation, which made English dependent on word order and function words to signal the relation of words in a sentence. The major phonetic changes that have shifted English are the change of final /m/ to /n/, the leveling of unstressed vowels, the loss of final /n/, and the decay of schwa in final syllables. These changes led to reduction of inflections of English as well as the loss of grammatical gender. The operation of analogy, the tendency of language to follow certain patterns and to adapt a less common form to a more familiar one, has also played an important role in changing English.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.235-242
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• 2017

Peaks (or Nulls) finding algorithms for Average Magnitude Difference Function (AMDF) of speech signal are proposed in this paper. Both AMDF and Autocorrelation Function (ACF) are widely used to estimate a pitch of speech signal. It is well known that the estimation of the fundamental requency (F0) for speech signal is not only important but also very difficult. In this paper, two algorithms, are exploited the characteristics of AMDF, are proposed. First, the proposed algorithm which has a Threshold value is applied to the local minima to detect a pitch period. The Other proposed algorithm to estimate a pitch period of speech signal is utilized the relationship between AMDF and ACF. The data in this paper, is recorded by using general commercial device, is composed of Korean emotion expression words. The recorded speech data are applied to two proposed algorithms and tested their performance.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.603-606
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• 1998

In a large number of words and the continued speech recognition system using a phoneme as teh recognition unit, it is necessary to segment processing. In this paper, a normalized AMDF new method. The suggested parameter represents a degree of sharpness at valley point. This method can detect the speech segment between the steady state and transient region to the continued speech without a prior information of speech signal.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.46-49
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• 2003

The use of confidence measures for word/utterance verification has become art essential component of any speech input application. Confidence measures have applications to a number of problems such as rejection of incorrect hypotheses, speaker adaptation, or adaptive modification of the hypothesis score during search in continuous speech recognition. In this paper, we present a new utterance verification method using vowel string. Using subword HMMs of VCCV unit, we create anti-models which include vowel string in hypothesis words. The experiment results show that the utterance verification rate of the proposed method is about 79.5%.

• Speech Sciences
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• v.5 no.1
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• pp.63-80
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• 1999

In this paper, an adaptive method of dividing a speech signal into an initial, a medial and a final sound of the form of utterance utilized by evaluating extreme limits of short term energy and autocorrelation functions. By applying this method into speech signal composed of a consonant, a vowel and a consonant, it was divided into an initial, a medial and a final sound and its feature analysis of sample by LPC were carried out. As a result of spectrum analysis in each period, it was observed that there existed spectrum features of a consonant and a vowel in the initial and medial periods respectively and features of both in a final sound. Also, when all kinds of words were adaptively divided into 3 periods by using the proposed method, it was found that the initial sounds of the same consonant and the medial sounds of the same vowels have the same spectrum characteristics respectively, but the final sound showed different spectrum characteristics even if it had the same consonant as the initial sound.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.289-297
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• 2003

The performance of a bimodal system is affected by the accuracy of the endpoint detection from the input signal as well as the performance of the speech recognition or lipreading system. In this paper, we propose the endpoint detection method which detects the endpoints from the audio and video signal respectively and utilizes the signal to-noise ratio (SNR) estimated from the input audio signal to select the reliable endpoints to the acoustic noise. In other words, the endpoints are detected from the audio signal under the high SNR and from the video signal under the low SNR. Experimental results show that the bimodal system using the proposed endpoint detector achieves satisfactory recognition rates, especially when the acoustic environment is quite noisy.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.81-84
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• 2000

In this paper, a new technology for extracting the feature of the speech signal of an isolated word by the analysis on the frequency domain is proposed. This technology can be applied efficiently for the limited speech domain. In order to extract the feature of speech signal, the number of peaks is calculated and the value of the frequency for a peak is used. Then the difference between the maximum peak and the second peak is also considered to identify the meanings among the words in the limited domain. By implementing this process hierarchically, the feature of speech signal can be extracted more quickly.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.117-124
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• 2011

This study investigated the effects of the types of noise and signal to noise ratios (SNRs) on speech intelligibility of an adult with dysartrhia. Speech intelligibility was judged by 48 naive listeners using a word transcription task. Repeated measures design was used with the types of noise (multi-talker babble/environmental noise) and SNRs (0, +10 dB, +20 dB) as within-subject factors. The dependent measure was the percentage of correctly transcribed words. Results revealed that two main effects were statistically significant. Listeners performed significantly worse in the multi-talker babble condition than the environmental noise condition, and they performed significantly better at higher levels of SNRs. The current results suggested that the multi-talker babble and lower level of SNRs decreased the speech intelligibility of adults with dysarthria, and speech-language pathologists should consider environmental factors such as the types of noise and SNRs in evaluating speech intelligibility of adults with dysarthria.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.118-127
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• 1998

In this paper, we propose a voice personality transformation method which makes one person's voice sound like another person's voice. In order to transform the voice personality, vocal tract transfer function is used as a transformation parameter. Comparing with previous methods, the proposed method can obtain high-quality transformed speech with low computational complexity. Conversion between the vocal tract transfer functions is implemented by a linear mapping based on soft clustering. In this process, mean LPC cepstrum coefficients and mean removed LPC cepstrum modeled by the low dimensional vector are used as transformation parameters. To evaluate the performance of the proposed method, mapping rules are generated from 61 Korean words uttered by two male and one female speakers. These rules are then applied to 9 sentences uttered by the same persons, and objective evaluation and subjective listening tests for the transformed speech are performed.

• Proceedings of the KSRS Conference
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• v.1
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• pp.79-81
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• 2006

Geostationary ocean satellite, unlike other sun-synchronous polar-orbit satellites, will be able to take a picture of a large region several times a day (almost with every one hour interval). For geostationary satellite, the target region is fixed though the location of sun is changed always. Thus, the ocean signal of a given target point is largely dependent on time. In other words, the ocean signal detected by geostationary satellite sensor must translate to the signal of target when both sun and satellite are located in nadir, using another correction model. This correction is performed with a standardization of signal throughout relative geometric relationship among satellite - sun - target points. One signal value of a selected pixel point of the target region of Geostationary Ocean Colour Imager (GOCI) would be set up as a standard, and the ratio of all remained pixel point can be calculated. This relative ratio called bidirectional factor, the result of modelling of spatiotemporal variation of bidirectional factor is shown.