This study examines personal factors that affect Korean speakers' English pronunciation. Personal factors which are examined here are as follows: personality type, cognitive system, motivational orientation type, interest in English, how often they listen to tapes, and academic achievements. Data were collected through MBTI (Myers Briggs Type Indicator) Test, Group Embedded Figural Test, and a Questionnaire. The participants consisted of 65 college students. All the results were statistically analyzed: Korean students' personality type and cognitive system are not related with their pronunciation, but motivational orientation type, how often they listen to tapes, academic achievements, and interest in English study are correlated with their pronunciation.

This paper investigates differences between generations in the vowel system of the Daegu dialect in terms of F1 and F2 of the monophthongs. Three different groups of subjects participated in the present study: 20 female native speakers of the Daegu dialect(10 in their 20's and 10 in their 40's), and 10 female native speakers of the Seoul dialect as a control group. It has been assumed that the Daegu dialect has six vowels. However, younger generation appears to have 7 vowels different from older generation. The result of the present study showed that the Daegu dialect has different vowel systems between generations: for 40's have six vowels and 20's have seven vowels. These differences seems to be attributed to the influence of the Seoul dialect.

The purpose of this study is to observe how Korean learners perceive an English weak syllable in words containing WS syllable pattern. According to the automated discrimination task using E-Prime, the ratio of correct answer(%) and reaction time of the stimuli with same syllable patterns were respectively higher and faster than those with different syllable patterns. Specifically, in the stimuli with different syllable patterns, the frequency(familiarity) of stressed word succeeding weak syllable and whether the weak syllable had coda in it were two important factors in distinguishing between a word with and without weak syllable. Even though the high English proficiency Koreans had faster reaction time than the low English proficiency Koreans, all Korean learners had a difficulty in perceiving the weak syllable at the beginning of a word.

This study aims to investigate whether Chinese learning Korean and Korean native speakers show any difference in length and formant structures of the Korean liquid 'ㄹ' in the environments of v_v and v_# through the acoustic analysis of 10 Chinese learners' and 10 Koreans' utterances. The acoustic analysis of L2KSC DB shows that the length and formant structures of 'ㄹ' produced by Chinese learners are significantly different from the ones by Koreans. I explain these differences by contrasting the liquids and syllable structure constraints of the two languages, Chinese and Korean. In addition, I relate the F1 and F2's values to the tongue's movement when making a constriction, and conclude that Chinese learners pronounce the 'ㄹ' in the v_# environment with the tongue lower and backer than Koreans do.

The purpose of this study was to see whether Korean-English bilinguals' semantic systems of Korean and English are shared or separated between the two languages. In a series of picture-word interference tasks, participants were required to name the pictures in Korean or in English with distractor words printed either in Korean or English. The distractor words were any of identical, semantically related, or neutral to the picture. The response time of naming was facilitated when distractor words were semantically identical for both same- and different-language pairs. But this facilitation effect was stronger when naming was produced in their native language, which in this case was Korean. Also, inhibitory effect was found when the picture and its distractor word were semantically related in both same- and different-language paired conditions. From these results it can be concluded that semantic representations of Korean and English may not be entirely but partly overlapping in bilinguals.

The purpose of this study was to explore the acoustic characteristics of sexy voice. In this study, we measured acoustic parameters (fundamental frequency, jitter, shimmer, and nasalance) of a sustained vowel sound produced by 40 actors (20 males and 20 females) and 40 non-actors (20 males and 20 females). Digital audio recordings were made in the sustained vowel |a| for acoustic analyses using Praat (version 4.1.9) and Nasal View (version 4.5). Twenty voice pathologists participated in the listening experiment and judged the degree of sexiness on a 7-point scale. The results showed that fundamental frequency, shimmer and nasalance had significant differences between actors and non-actors. The acoustic parameters of sexy voice matched perceptual aspects of a previous study: Low fundamental frequency-low pitch and high shimmer-husky voice. On the other hand, the nasalance score did not match that of the previous study: Decreased nasalance had a higher score on sexiness scale judged by the listeners. It would be desirable to study the voice quality by analyzing and controlling more acoustic and auditory parameters for practical applications in the future.

This paper suggests an algorithm that can estimate the direction of the sound source in real time. The algorithm uses the time difference and sound intensity information among the recorded sound source by four microphones. Also, to deal with noise of robot itself, the Kalman filter is implemented. The proposed method can take shorter execution time than that of an existing algorithm to fit the real-time service robot. Also, using the Kalman filter, signal ratio relative to background noise, SNR, is approximately improved to 8 dB. And the estimation result of azimuth shows relatively small error within the range of ${\pm}7$ degree.

In this paper, we introduce two retrieval methods for photos with speech documents. We compare the pattern of speech query with those of speech documents recorded in digital cameras, and measure the similarities, and retrieve photos corresponding to the speech documents which have high similarity scores. As the first approach, a phoneme recognition scheme is used as the pre-processor for the pattern matching, and in the second one, the vector quantization (VQ) and the dynamic time warping (DTW) are applied to match the speech query with the documents in signal domain itself. Experimental results show that the performance of the first approach is highly dependent on that of phoneme recognition while the processing time is short. The second method provides a great improvement of performance. While the processing time is longer than that of the first method due to DTW, but we can reduce it by taking approximated methods.

Recently, many studies have been done for speech recognition in noisy environments. Particularly, the Aurora DB has been built as the common database for comparing the various feature extraction schemes. However, in general, the recognition models as well as the features have to be modified for effective noisy speech recognition. As the structure of the HTK is very complex, it is not easy to modify, the recognition engine. In this paper, we implemented a baseline recognizer based on the segmental K-means algorithm whose performance is comparable to the HTK in spite of the simplicity in its implementation.

This paper aims to propose a method of detecting irregular pronunciations for Korean POI data adopting the notion of the Prosodic Word based on the Prosodic Phonology (Selkirk 1984, Nespor and Vogel 1986) and Intonational Phonology (Jun 1996). In order to show the performance of the proposed method, the detection experiment was conducted on the 250,000 POI data. When all the data were trained, 99.99% of the exceptional prosodic words were detected, which shows the stability of the system. The results show that similar ratio of exceptional prosodic words (22.4% on average) were detected on each stage where a certain amount of the training data were added. Being intended to be an example of an interdisciplinary study of linguistics and computer science, this study will, on the one hand, provide an understanding of Korean language from the phonological point of view, and, on the other hand, enable a systematic development of a multiple pronunciation lexicon for Korean TTS or ASR systems of high performance.

In this paper, we present a phrase break prediction method using CRF(Conditional Random Fields), which has good performance at classification problems. The phrase break prediction problem was mapped into a classification problem in our research. We trained the CRF using the various linguistic features which was extracted from POS(Part Of Speech) tag, lexicon, length of word, and location of word in the sentences. Combined linguistic features were used in the experiments, and we could collect some linguistic features which generate good performance in the phrase break prediction. From the results of experiments, we can see that the proposed method shows improved performance on previous methods. Additionally, because the linguistic features are independent of each other in our research, the proposed method has higher flexibility than other methods.

The MMSE-STSA based speech enhancement algorithm is widely used as a preprocessing for noise robust speech recognition. It weighs the gain of each spectral bin of the noisy speech using the estimate of noise and signal power spectrum. In this paper, we investigate the influence of parameters used to estimate the speech signal and noise power in MMSE-STSA upon the recognition performance of noisy speech. For experiments, we use the Aurora2 DB which contains noisy speech with subway, babble, car, and exhibition noises. The HTK-based continuous HMM system is constructed for recognition experiments. Experimental results are presented and discussed with our findings.

In this paper we use a training algorithm, MCE (Minimum Classification Error), to improve the performance of a text-independent speaker identification system. The MCE training scheme takes account of possible competing speaker hypotheses and tries to reduce the probability of incorrect hypotheses. Experiments performed on a small set speaker identification task show that the discriminant training method using MCE can reduce identification errors by up to 54% over a baseline system trained using Bayesian adaptation to derive GMM (Gaussian Mixture Models) speaker models from a UBM (Universal Background Model).

Because a packet loss brings about degradation of speech quality, VoIP speech coders have PLC (Packet Loss Concealment) mechanism. G.711, which is a mandatory VoIP speech coder, also has the PLC algorithm based on pitch period replication. However, it is not robust to burst losses. Thus, we propose two methods to improve the performance of the original PLC algorithm in G.711. One adaptively utilizes voiced/unvoiced information of adjacent good frames regarding to the current lost frame. The other is based on adaptive gain control according to energy variation across the frames. We evaluate the performance of the proposed PLC algorithm by measuring a PESQ value under different random and burst packet loss simulating conditions. It is shown from the experiments that the performance of the proposed PLC algorithm outperforms that of PLC employed in ITU-T Recommendation G.711.