• Phonetics and Speech Sciences
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• v.6 no.3
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• pp.57-62
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• 2014

The present study was performed to investigate and discuss the aerodynamic characteristics of whispered and normal speech during reading paragraph tasks. 39 normal females(18-23 yrs.) read 'Autumn' paragraph with whispered and normal phonation. Their readings were recorded and analyzed by 'Running Speech' in Phonatory Aerodynamic System(PAS) instrument. As results, during whispered speech, the total duration was longer and the numbers of inspiration were more frequently shown than normal speech. The Peak expiratory and inspiratory rate were higher in normal speech, but the expiratory and inspiratory volume were higher in whispered speech. By correlation analysis, both whispered and normal speech showed significantly high correlation between total duration and expiratory/inspiratory airflow duration; numbers of inspiration and inspiratory airflow duration; expiratory and inspiratory volume. These results show that whispered speech needs more respiratory effort but shows poorer aerodynamic efficacy during phonation than normal speech.

• The Journal of the Acoustical Society of Korea
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• v.14 no.5
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• pp.51-57
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• 1995

In this paper, we study a noise-robust feature extraction method of speech signal based on auditory modeling. The auditory model consists of a basilar membrane, a hair cell model and spectrum output stage. Basilar membrane model describes a response characteristic of membrane according to vibration in speech wave, and is represented as a band-pass filter bank. Hair cell model describes a neural transduction according to displacements of the basilar membrane. It responds adaptively to relative values of input and plays an important role for noise-robustness. Spectrum output stage constructs a mean rate spectrum using the average firing rate of each channel. And we extract feature vectors using a mean rate spectrum. Simulation results show that when auditory-based feature extraction is used, the speech recognition performance in noisy environments is improved compared to other feature extraction methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.784-788
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• 2008

In this research, we propose a remote speech input unit, a new method of user-friendly speech input in speech recognition system. We focused the user friendliness on hands-free and microphone independence in speech recognition applications. Our module adopts two algorithms, the automatic speech detection and speech enhancement based on the microphone array-based beamforming method. In the performance evaluation of speech detection, within-200msec accuracy with respect to the manually detected positions is about 97percent under the noise environments of 25dB of the SNR. The microphone array-based speech enhancement using the delay-and-sum beamforming algorithm shows about 6dB of maximum SNR gain over a single microphone and more than 12% of error reduction rate in speech recognition.

• Phonetics and Speech Sciences
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• v.13 no.3
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• pp.15-20
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• 2021

In line with recent attention to the multimodal expression of politeness, the present study examined the association between polite speech and acoustic features through the analysis of vowels produced in casual and polite speech contexts in Korean. Fourteen adult native speakers of Seoul Korean produced the utterances in two social conditions to elicit polite (professor) and casual (friend) speech. Vowel duration and the first (F1) and second formants (F2) of seven sentence- and phrase-initial monophthongs were measured. The results showed that polite speech shares acoustic similarities with vowel production in clear speech: speakers showed greater vowel space expansion in polite than casual speech in an effort to enhance perceptual intelligibility. Especially, female speakers hyperarticulated (front) vowels for polite speech, independent of speech rate. The implications for the acoustic encoding of social stance in polite speech are further discussed.

• ETRI Journal
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• v.43 no.1
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• pp.82-94
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• 2021

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR-E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linear-predictive-coding-based speech analysis-synthesis system and their performance has been compared in terms of the percentage of the voiced/unvoiced classification accuracy, speech quality, and computation time. The results of the percentage of the voiced/unvoiced classification accuracy and speech quality show that the NN-based speech classifier performs better than the ACF-, AMDF-, cepstrum-, WACF- and ZCR-E-based speech classifiers for both clean and noisy environments. The computation time results show that the AMDF-based speech classifier is computationally simple, and thus its computation time is less than that of other speech classifiers, while that of the NN-based speech classifier is greater compared with other classifiers.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.568-574
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• 2010

In an effort to improve the speech recognition rate, we investigated performance comparison between speaker-independent and gender-specific speech recognitions. For this purpose, 20 male and 20 female speakers each pronounced 300 isolated Korean words and the speeches were divided into 4 groups: female, male, and two mixed genders. To examine the validity for the gender-specific speech recognition, Fourier spectrum and MFCC feature vectors averaged over male and female speakers separately were examined. The result showed distinction between the two genders, which supports the motivation for the gender-specific speech recognition. In experiments of speech recognition rate, the error rate for the gender-specific case was shown to be less than50% compared to that of the speaker-independent case. From the obtained results, it might be suggested that hierarchical recognition of gender and speech recognition might yield better performance over the current method of speech recognition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3267-3274
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• 2011

Recently, speech recognition technology has dramatically developed, with the increase in the user environment of various mobile devices and influence of a variety of speech recognition software. However, for speech recognition for multi-language, lack of understanding of multi-language lexical model and limited capacity of systems interfere with the improvement of the recognition rate. It is not easy to embody speech expressed with multi-language into a single acoustic model and systems using several acoustic models lower speech recognition rate. In this regard, it is necessary to research and develop a multi-language speech recognition system in order to embody speech comprised of various languages into a single acoustic model. This paper studied a system that can recognize Korean and English as International Phonetic Language (IPA), based on the research for using a multi-language acoustic model in mobile devices. Focusing on finding an IPA model which satisfies both Korean and English phonemes, we get 94.8% of the voice recognition rate in Korean and 95.36% in English.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.407-412
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• 2019

In this paper, we propose a technique for processing of speech recognition in korean words. Speech recognition is a technology that converts acoustic signals from sensors such as microphones into words or sentences. Most foreign languages have less difficulty in speech recognition. On the other hand, korean consists of vowels and bottom consonants, so it is inappropriate to use the letters obtained from the voice synthesis system. That improving the conventional structure speech recognition can the correct words recognition. In order to solve this problem, a new algorithm was added to the existing speech recognition structure to increase the speech recognition rate. Perform the preprocessing process of the word and then token the results. After combining the result processed in the Levenshtein distance algorithm and the hashing algorithm, the normalized words is output through the consonant comparison algorithm. The final result word is compared with the standardized table and output if it exists, registered in the table dose not exists. The experimental environment was developed by using a smartphone application. The proposed structure shows that the recognition rate is improved by 2% in standard language and 7% in dialect.

• The Journal of the Acoustical Society of Korea
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• v.4 no.1
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• pp.9-15
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• 1985

In this paper, we describe a new algorithm for deciding whether a given segment of a speech signal is classified as voiced speech, unvoiced speech, or silence, based on parameters made on the signal. The measured parameters for the voiced-unvoiced classfication are the areas of each Zero crossing interval, which is given by multiplication of the magnitude by the inverse zero corssing rate of speech signals. The employed parameter for the unvoiced-silence classification, also, are each of positive area summation during four milisecond interval for the high frequency emphasized speech signals.

• Speech Sciences
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• v.7 no.2
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• pp.19-35
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• 2000

Speech evaluation and treatment planning for the patients with articulation disorders have traditionally been based on perceptual judgement by speech pathologists. Recently, various computerized speech analysis systems have been developed and commonly used in clinical settings to obtain the objective and quantitative data and specific treatment strategies. 10 dysarthric children (6 neurogenic and 4 functional dysarthria) participated in this experiment. Speech evaluation of dysarthria was performed in two ways; first, the acoustic analysis by Visi-Pitch and a Computerized Speech Lab and second, the perceptual scoring of phonetic errors rates in 100 word test. The results of the initial evaluation served as primary guidlines for the indivisualized treatment planning of each patient's speech problems. After mean treatment period of 5 months, the follow-up data of both dysarthric groups showed increased maximum phonation time, increased alternative motion rate and decreased occurrence of articulatory deviation. The changes of acoustic data and therapeutic effects were more prominent in children with dysarthria due to neurologic causes than with functional dysarthria. Three cases including their pre- and post treatment data were illustrated in detail.