• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.681-686
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• 2012

This paper studied the speech parameters less affected by the human emotion for the development of the robust emotional speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient, root-cepstral coefficient, PLP coefficient and frequency warped mel-cepstral coefficient in the vocal tract length normalization method were used as feature parameters. And CMS (Cepstral Mean Subtraction) and SBR(Signal Bias Removal) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using frequency warped RASTA mel-cepstral coefficient in the vocal tract length normalized method, its derivatives and CMS as a signal bias removal showed the best performance.

• ETRI Journal
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• v.32 no.2
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• pp.345-347
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• 2010

In this letter, we present a new speech hash function based on the non-negative matrix factorization (NMF) of linear prediction coefficients (LPCs). First, linear prediction analysis is applied to the speech to obtain its LPCs, which represent the frequency shaping attributes of the vocal tract. Then, the NMF is performed on the LPCs to capture the speech's local feature, which is then used for hash vector generation. Experimental results demonstrate the effectiveness of the proposed hash function in terms of discrimination and robustness against various types of content preserving signal processing manipulations.

• Phonetics and Speech Sciences
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• v.6 no.1
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• pp.71-76
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• 2014

In this paper voice quality of normal speech is qualitatively classified by five components of breathy, creaky, rough, nasal, and thin/thick voice. To determine whether a correlation exists between a subjective measure of voice and an objective measure of voice, each voice is perceptually evaluated using the 1/2/3 scale by speech processing specialists and acoustically analyzed using speech analysis tools such as the Praat, MDVP, and VoiceSauce. The speech parameters include features related to speech source and vocal tract filter. Statistical analysis uses a two-independent-samples non-parametric test. Experimental results show that statistical analysis identified a significant correlation between the speech feature parameters and the components of voice quality.

• MALSORI
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• no.51
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• pp.1-16
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• 2004

The aim of this paper is to analyze vowels in voice imitation and disguised voice, and to find the invariable phonetic features of the speaker. In this paper we examined the formants of monophthongs /a, u, i, o, {$\omega},{\;}{\varepsilon},{\;}{\Lambda}$/. The results of the present are as follows : $\circled1$ Speakers change their vocal tract features. $\circled2$ Vowels /a, ${\varepsilon}$, i/ appear to be proper for speaker recognition since they show invariable acoustic feature during voice modulation. $\circled3$ F1 does not change easily compared to higher formants. $\circled4$ F3-F2 appears to be constituent for a speaker identification in vowel /a/ and /$\varepsilon$/, and F4-F2 in vowel /i/. $\circled5$ Resulting of F-ratio, differences of each formants were more useful than individual formant of a vowel to speaker recognition.

• Speech Sciences
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• v.10 no.1
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• pp.3-13
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• 2003

The devoicing vowel is a phonological process whose contrast in sonority is lost or reduces in a particular phonetic environment. Phonetically, the vocal fold vibration originates from the abduction/adduction of the glottis in relation to supraglottal articulatory movements. The purpose of this study is to investigate Korean vowel devoicing by means of experimental instruments. The interrelated laryngeal adjustments and aerodynamic effects for this voicing can clarify the redundant articulatory gestures relevant to the distinctive feature of sonority. Five test words were selected, being composed of the high vowel /i/, between the fricative and strong aspirated or lenis affricated consonants. The subjects uttered the test words successively at a normal or at a faster speed. The EMG, the sensing tube Gaeltec S7b and the High-Speech Analysis system and MSL II were used in these studies. Acoustically, three different types of speech waveforms and spectrograms were classified, based on the voicing variation. The intraoral air pressure curves showed differences, depending on the voicing variations. The activity patterns of the PCA and the CT for devoicing vowels appeared differently from those showing the partially devoicing vowels and the voicing vowels.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3119-3127
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• 2000

This paper is a study to find a new method of feature selection for vibrationof buman body by analyzing correlationof vibration between King Songdok Bell and Human body. The vibration characteristics are analyzed by matching body, vocal tract, diaphragm and asymmetrical clements of human body with Bell, resonator, hole in the ground and asymmetical elements. In the result, the characteristics of sound vibrationof King Songdok Bell is useful to apply it to vibration characteristics of human body because the vibration characteristics of ech elements is alike.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.400-409
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• 2004

In this paper. a voice personality transformation method is proposed. which makes one person's voice sound like another person's voice. To transform the voice personality. vocal tract transfer function is used as a transformation parameter. Comparing with previous methods. the proposed method makes transformed speech closer to target speaker's voice in both subjective and objective points of view. Conversion between vocal tract transfer functions is implemented by classification of entire vector space followed by linear transformation for each cluster. LPC cepstrum is used as a feature parameter. A joint classification and transformation method is proposed, where optimum clusters and transformation matrices are simultaneously estimated in the sense of a minimum mean square error criterion. To evaluate the performance of the proposed method. transformation rules are generated from 150 sentences uttered by three male and on female speakers. These rules are then applied to another 150 sentences uttered by the same speakers. and objective evaluation and subjective listening tests are performed.

• Speech Sciences
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• v.1
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• pp.153-200
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• 1997

In languages such as Japanese, it is very common to observe that short peripheral vowel are completely voiceless when surrounded by voiceless consonants. This phenomenon has been known as Montreal French, Shanghai Chinese, Greek, and Korean. Traditionally this phenomenon has been described as a phonological rule that either categorically deletes the vowel or changes the [+voice] feature of the vowel to [-voice]. This analysis was supported by Sawashima (1971) and Hirose (1971)'s observation that there are two distinct EMG patterns for voiced and devoiced vowel in Japanese. Close examination of the phonetic evidence based on acoustic data, however, shows that these phonological characterizations are not tenable (Jun & Beckman 1993, 1994). In this paper, we examined the vowel devoicing phenomenon in Korean using data from ENG fiberscopic and acoustic recorders of 100 sentences produced by one Korean speaker. The results show that there is variability in the 'degree of devoicing' in both acoustic and EMG signals, and in the patterns of glottal closing and opening across different devoiced tokens. There seems to be no categorical difference between devoiced and voiced tokens, for either EMG activity events or glottal patterns. All of these observations support the notion that vowel devoicing in Korean can not be described as the result of the application of a phonological rule. Rather, devoicing seems to be a highly variable 'phonetic' process, a more or less subtle variation in the specification of such phonetic metrics as degree and timing of glottal opening, or of associated subglottal pressure or intra-oral airflow associated with concurrent tone and stricture specifications. Some of token-pair comparisons are amenable to an explanation in terms of gestural overlap and undershoot. However, the effect of gestural timing on vocal fold state seems to be a highly nonlinear function of the interaction among specifications for the relative timing of glottal adduction and abduction gestures, of the amplitudes of the overlapped gestures, of aerodynamic conditions created by concurrent oral tonal gestures, and so on. In summary, to understand devoicing, it will be necessary to examine its effect on phonetic representation of events in many parts of the vocal tracts, and at many stages of the speech chain between the motor intent and the acoustic signal that reaches the hearer's ear.

• Journal of Oral Medicine and Pain
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• v.30 no.4
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• pp.427-432
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• 2005

This study have been compared and analyzed voice parameter under the condition of normal voice and auditory condition(noise and music) for 29 patients of orofacial pain and 31 normal people to investigate voice feature and vocal variation for auditory condition of orofacial pain patient. 1. Compared to normal voice, orofacial pain patient showed lower and unstable voice feature which has low F0 rate and high jitter and shimmer rate. 2. Voice of orofacial pain patient showed more relaxed and stable voice feature with low F0 and shimmer rate in the music condition than noise condition. 3. Normal people's voice has no significant difference between music and noise condition even though it has high F0 rate under the noise condition. As a result, orofacial pain patient showed difference of feature and different response for external auditory condition compared to normal voice. Providing of positive emotional environment such as music could be considered for better outcome of oral facial pain patient's functional disability.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.226-234
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• 2007

In this paper, we develop a speech recognition system using a throat microphone. The use of this kind of microphone minimizes the impact of environmental noise. However, because of the absence of high frequencies and the partially loss of formant frequencies, previous systems developed with those devices have shown a lower recognition rate than systems which use standard microphone signals. This problem has led to researchers using throat microphone signals as supplementary data sources supporting standard microphone signals. In this paper, we present a high performance ASR system which we developed using only a throat microphone by taking advantage of Korean Phonological Feature Theory and a detailed throat signal analysis. Analyzing the spectrum and the result of FFT of the throat microphone signal, we find that the conventional MFCC feature vector that uses a critical pass filter does not characterize the throat microphone signals well. We also describe the conditions of the feature extraction algorithm which make it best suited for throat microphone signal analysis. The conditions involve (1) a sensitive band-pass filter and (2) use of feature vector which is suitable for voice/non-voice classification. We experimentally show that the ZCPA algorithm designed to meet these conditions improves the recognizer's performance by approximately 16%. And we find that an additional noise-canceling algorithm such as RAST A results in 2% more performance improvement.