• Title/Summary/Keyword: categorical boundary

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Effect of Music Training on Categorical Perception of Speech and Music

  • L., Yashaswini;Maruthy, Sandeep
    • Journal of Audiology & Otology
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    • v.24 no.3
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    • pp.140-148
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    • 2020
  • Background and Objectives: The aim of this study is to evaluate the effect of music training on the characteristics of auditory perception of speech and music. The perception of speech and music stimuli was assessed across their respective stimulus continuum and the resultant plots were compared between musicians and non-musicians. Subjects and Methods: Thirty musicians with formal music training and twenty-seven non-musicians participated in the study (age: 20 to 30 years). They were assessed for identification of consonant-vowel syllables (/da/ to /ga/), vowels (/u/ to /a/), vocal music note (/ri/ to /ga/), and instrumental music note (/ri/ to /ga/) across their respective stimulus continuum. The continua contained 15 tokens with equal step size between any adjacent tokens. The resultant identification scores were plotted against each token and were analyzed for presence of categorical boundary. If the categorical boundary was found, the plots were analyzed by six parameters of categorical perception; for the point of 50% crossover, lower edge of categorical boundary, upper edge of categorical boundary, phoneme boundary width, slope, and intercepts. Results: Overall, the results showed that both speech and music are perceived differently in musicians and non-musicians. In musicians, both speech and music are categorically perceived, while in non-musicians, only speech is perceived categorically. Conclusions: The findings of the present study indicate that music is perceived categorically by musicians, even if the stimulus is devoid of vocal tract features. The findings support that the categorical perception is strongly influenced by training and results are discussed in light of notions of motor theory of speech perception.

Effect of Music Training on Categorical Perception of Speech and Music

  • L., Yashaswini;Maruthy, Sandeep
    • Korean Journal of Audiology
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    • v.24 no.3
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    • pp.140-148
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    • 2020
  • Background and Objectives: The aim of this study is to evaluate the effect of music training on the characteristics of auditory perception of speech and music. The perception of speech and music stimuli was assessed across their respective stimulus continuum and the resultant plots were compared between musicians and non-musicians. Subjects and Methods: Thirty musicians with formal music training and twenty-seven non-musicians participated in the study (age: 20 to 30 years). They were assessed for identification of consonant-vowel syllables (/da/ to /ga/), vowels (/u/ to /a/), vocal music note (/ri/ to /ga/), and instrumental music note (/ri/ to /ga/) across their respective stimulus continuum. The continua contained 15 tokens with equal step size between any adjacent tokens. The resultant identification scores were plotted against each token and were analyzed for presence of categorical boundary. If the categorical boundary was found, the plots were analyzed by six parameters of categorical perception; for the point of 50% crossover, lower edge of categorical boundary, upper edge of categorical boundary, phoneme boundary width, slope, and intercepts. Results: Overall, the results showed that both speech and music are perceived differently in musicians and non-musicians. In musicians, both speech and music are categorically perceived, while in non-musicians, only speech is perceived categorically. Conclusions: The findings of the present study indicate that music is perceived categorically by musicians, even if the stimulus is devoid of vocal tract features. The findings support that the categorical perception is strongly influenced by training and results are discussed in light of notions of motor theory of speech perception.

Predictive Spatial Data Fusion Using Fuzzy Object Representation and Integration: Application to Landslide Hazard Assessment

  • Park, No-Wook;Chi, Kwang-Hoon;Chung, Chang-Jo;Kwon, Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.19 no.3
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    • pp.233-246
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    • 2003
  • This paper presents a methodology to account for the partial or gradual changes of environmental phenomena in categorical map information for the fusion/integration of multiple spatial data. The fuzzy set based spatial data fusion scheme is applied in order to account for the fuzziness of boundaries in categorical information showing the partial or gradual environmental impacts. The fuzziness or uncertainty of boundary is represented as two kinds of fuzzy membership functions based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of a cross validation procedure. A case study for landslide hazard assessment demonstrates the better performance of this scheme as compared to traditional crisp boundary representation.

Bayesian approach for categorical Table with Nonignorable Nonresponse

  • Choi, Bo-Seung;Park, You-Sung
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.59-65
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    • 2005
  • We propose five Bayesian methods to estimate the cell expectation in an incomplete multi-way categorical table with nonignorable nonresponse mechanism. We study 3 Bayesian methods which were previously applied to one-way categorical tables. We extend them to multi-way tables and, in addition, develop 2 new Bayesian methods for multi-way categorical tables. These five methods are distinguished by different priors on the cell probabilities: two of them have the priors determined only by information of respondents; one has a constant prior; and the remaining two have priors reflecting the difference in the response mechanisms between respondent and non-respondent. We also compare the five Bayesian methods using a categorical data for a prospective study of pregnant women.

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Complex Segregation Analysis of Categorical Traits in Farm Animals: Comparison of Linear and Threshold Models

  • Kadarmideen, Haja N.;Ilahi, H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.18 no.8
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    • pp.1088-1097
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    • 2005
  • Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

Categorical Perception in intonation

  • Lee, Ho-Young
    • Proceedings of the KSPS conference
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    • 2002.11a
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    • pp.86-89
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    • 2002
  • According to Pierrehumbert (1980), two level tones - H and L - are enough in representing intonation of intonational languages. But in Korean, high fall and low fall boundary tones, both of which must be represented as HL% in intonational phonology as in Jun (1993, 1999), are distinct not only acoustically but also functionally. The same is true in the case of high level and mid level boundary tones, which must be represented as H% in intonational phonology. In this paper, I conducted two identification tests to provide crucial evidence that H and L are not enough in intonational phonology. The results of the identification tests show that categorical perception occur between high level and low level as well as between high fall and low fall. Based on this fact and the results of the acoustic analyses in Lee (1999, 2000), I strongly propose to adopt one more level tone - M - to represent Korean boundary tones.

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Gradient Reduction of $C_1$ in /pk/ Sequences

  • Son, Min-Jung
    • Speech Sciences
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    • v.15 no.4
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    • pp.43-60
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    • 2008
  • Instrumental studies (e.g., aerodynamic, EPG, and EMMA) have shown that the first of two stops in sequence can be articulatorily reduced in time and space sometimes; either gradient or categorical. The current EMMA study aims to examine possible factors_linguistic (e.g., speech rate, word boundary, and prosodic boundary) and paralinguistic (e.g., natural context and repetition)_to induce gradient reduction of $C_1$ in /pk/ cluster sequences. EMMA data are collected from five Seoul-Korean speakers. The results show that gradient reduction of lip aperture seldom occurs, being quite restricted both in speaker frequency and in token frequency. The results also suggest that the place assimilation is not a lexical process, implying that speakers have not fully developed this process to be phonologized in the abstract level.

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Categorical Analysis for Finite Cellular Automata Rule 15 (유한 셀룰러 오토마타 규칙 15에 대한 카테고리적 분석)

  • Park, Jung-Hee;Lee, Hyen-Yeal
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.8
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    • pp.752-757
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    • 2000
  • The recursive formulae, which can self-reproduce the state transition graphs, of one-dimensional cellular automata rule 15 with two states (0 and 1) and four different boundary conditions were founded by categorical access. The categorical access makes the evolution process for cellular automata be expressed easily since it enables the mapping of automata between different domains.

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Effects of Uncertain Spatial Data Representation on Multi-source Data Fusion: A Case Study for Landslide Hazard Mapping

  • Park No-Wook;Chi Kwang-Hoon;Kwon Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.21 no.5
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    • pp.393-404
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    • 2005
  • As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

A Fuzzy Clustering Algorithm for Clustering Categorical Data (범주형 데이터의 분류를 위한 퍼지 군집화 기법)

  • Kim, Dae-Won;Lee, Kwang-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.661-666
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    • 2003
  • In this paper, the conventional k-modes and fuzzy k-modes algorithms for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. The hard-type centroids of the traditional algorithms had difficulties in dealing with ambiguous boundary data, which might be misclassified and lead to thelocal optima. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. The distance measure between data and fuzzy centroids is more precise and effective than those of the k-modes and fuzzy k-modes. To test the proposed approach, the proposed algorithm and two conventional algorithms were used to cluster three categorical data sets. The proposed method was found to give markedly better clustering results.