• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.11
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• pp.890-896
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• 2003

It is said that the goal of the design of good acoustical environment is at first the reduction of undesirable sounds. and in addition the introduction of desirable sounds by which our minds are soothed. The task of creating the desirable sounds leads to the realization of a comfortable acoustic environment and the design of soundscape. It may be an important starting point of soundscape design to select suitable sounds for the target spaces. because each space has a different surrounding condition and requires a special ambient sound. This paper aims to survey preference of the environmental sounds suitable for the public spaces in urban areas such as parks. bus terminals. 35 kinds of natural sounds are. rated by 26 pairs of adjectives. The results of psycho-acoustic experiments are as follows. 1. The proper adjectives for expressing the environmental sounds are classified into 6 groups of comfort, pleasure, fullness. variety, distinctness. and naturalness. 2. Bird singing. murmuring of a stream, artificial sounds. singing of insects and animals are the affirmative rank of preference. 3. Green musics consisted of music and natural sounds are preferred to the pure natural sounds. 4. Sound level relative to background noise causes various preferences to natural sounds in public spaces.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1010-1013
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• 2003

It is said that the goal of the design of good acoustical environment is at first the reduction of undesirable sounds, and in addition the introduction of desirable sounds by which our minds are soothed. The task of creating the desirable sounds leads to the realization of a comfortable acoustic environment and the design of soundscape. It may be an important starting point of soundscape design to select suitable sounds for the target spaces, because each space has a different surrounding condition and requires a special ambient sound. This paper aims to survey preference of the environmental sounds suitable for the public spaces in urban areas such as parks, bus terminals. 35 kinds of natural sounds are rated by 26 pairs of adjectives. The results of psycho-acoustic experiments are as follows. 1. The proper adjectives for expressing the environmental sounds are classified into 6 groups of comfort, pleasure, fullness, variety, distinctness, naturalness. 2. Bird singing, murmuring of a stream, artificial sounds, singing of insects and animals are the affirmative order of preference. 3. Green musics consisted of music and natural sounds are preferred to the pure natural sounds. 4. Sound level relative to background noise causes various preferences to natural sounds in public spaces.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.523-526
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• 2007

Currently, there are various sounds in the urban surrounding environment such as natural, human, mechanical or sound, etc., and these urban environmental sounds remain in several memories according to magnitude, repetition, learning and experience of sounds. However, there are limitations in memorizing these environmental sounds, thus they are forgotten or reminded, or replaced with new ones from time to time. This study was attempted to look into the changes of the memory of noisiness annoyance and sharpness of the suggested sound sources with urban environmental sounds as time goes by and the order of memorization of the sound sources.

• KIEAE Journal
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• v.8 no.1
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• pp.31-36
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• 2008

For the comfortable housing life, comfortable and pleasant urban environment should be created for the people living in house and in city. There are lots of environmental conditions in city affecting house and life. Also most of all the noise pollution have been become major factor that makes people's life uncomfortable. Recently soundscape researches have been performed to create comfortable urban environment and various studies on the evaluation of urban environmental sounds are now undergoing. This study aimed to analyse the subjective characteristics through the subjective evaluation to the sounds measured with physical parameters and eventually to find out alternative evaluation method for urban environmental sounds. Adjectives applied to previous studies were used for the subjective evaluation and sound sources recorded in specific places were presented with picture at the same time. As a result, new physical parameters such as Lmax, Unbiased Annoyance, G, N and EmT have a feasibility to evaluation of urban environment sounds in terms of acoustic comfort.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.670-673
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• 2005

For the comfortable housing life, an urban environment should give comfort and pleasantness to people living in house and in city. There are lots of environmental conditions in city affecting house and life and most of all the noise pollution have been become factor that makes people's life hard without need to say. Recently researches have been performed to create comfortable urban environment and a study on the evaluation of urban environmental sounds is now undergoing. This study aimed to analyse the subjective characteristics through the subjective evaluation to the sounds measured with physical parameters and eventually to find out evaluation method for urban environmental sounds. Vocabularies applied to previous studies were used for the subjective evaluation and sound sources recorded in specific places were presented with picture at the same time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.817-821
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• 2012

In this paper we applied the optimal mixture number estimation technique in GMM(Gaussian mixture model) using BIC(Bayesian information criterion) and MDL(minimum description length) as a model selection criterion for environmental sounds recognition. In the experiment, we extracted 12 MFCC(mel-frequency cepstral coefficients) features from 9 kinds of environmental sounds which amounts to 27747 data and classified them with GMM. As mentioned above, BIC and MDL is applied to estimate the optimal number of mixtures in each environmental sounds class. According to the experimental results, while the recognition performances are maintained, the computational complexity decreases by 17.8% with BIC and 31.7% with MDL. It shows that the computational complexity reduction by BIC and MDL is effective for environmental sounds recognition using GMM.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.497-503
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• 2011

In this paper, we proposed the MCE as a GMM training method to improve the performance of environmental sounds recognition. We model the environmental sounds data with newly defined misclassification function using the log likelihood of the corresponding class and the log likelihood of the rest classes for discriminative training. The model parameters are estimated with the loss function using GPD(generalized probabilistic descent). For recognition performance comparison, we extracted the 12 degrees features using preprocessing and MFCC(mel-frequency cepstral coefficients) of the 9 kinds of environmental sounds and carry out GMM classification experiments. According to the experimental results, MCE training method showed the best performance by an average of 87.06% with 19 mixtures. This result confirmed us that MCE training method could be effectively used as a GMM training method in environmental sounds recognition.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.810-813
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• 2004

The task of introducing sounds leads to the realization of a comfortable acoustic environment and the design of good soundscape. This paper aims to rate the preference of environmental sounds suitable to the public spaces such as park, garden, bus terminal, urban street. And aims to search for the methodology how to select the introducing sounds by subjective and objective procedures. Seventeen kinds of introducing sounds were rated by nine adjectives in the presence of visual site informations. Also adequate sound levels were calculated by adjusting the volume of introducing sounds in the presence of the background sounds and visual informations. The results of psycho-acoustic experiments are as follows. 1. Proposal of various introducing sounds were evaluated to be possible at the rather calm natural park. 2. The introducing sounds which have opposite visual image or already existing at the place were evaluated not adequate to the sound circumstances of the place. 3. By the sounds with the same meaning, the identity of the street and the improvement of sound circumstance can be obtained.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.734-737
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• 2006

For the comfortable housing life, an urban environment should give comfort and pleasantness to people living in house and in city. There are lots of environmental conditions in city affecting house and life and most of all the noise pollution have been become factor that makes people's life hard without need to say. Recently researches have been performed to create comfortable urban environment and a study on the evaluation of urban environmental sounds is now undergoing. This study aimed to analyse the subjective characteristics through the subjective evaluation to the sounds measured with physical parameters and eventually to find out evaluation method for urban environmental sounds. Vocabularies applied to previous studies were used for the subjective evaluation and sound sources recorded in specific places were presented with picture at the same time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3384-3398
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• 2020

In recent years, as the environment has become an important issue in dealing with food, energy, and urban development, diverse environment-related applications such as environmental monitoring and ecosystem management have emerged. In such applications, automatic classification of animals using video or sound is very useful in terms of cost and convenience. So far, many works have been done for animal sounds classification using artificial intelligence techniques such as a convolutional neural network. However, most of them have dealt only with the sound of a specific class of animals such as bird sounds or insect sounds. Due to this, they are not suitable for classifying various types of animal sounds. In this paper, we propose a sound classification scheme based on a multi-feature network for classifying sounds of multiple species of animals. To do that, we first collected multiple animal sound datasets and grouped them into classes. Then, we extracted their audio features by generating mixed records and used those features for training. To evaluate the effectiveness of our scheme, we constructed an animal sound classification model and performed various experiments. We report some of the results.