• The KIPS Transactions:PartD
• /
• v.10D no.3
• /
• pp.547-558
• /
• 2003

From the viewpoint of that music melody has the similar features to time-series data, music melody is transformed to a time-series data with normalization and corrections and the similarity between melodies is defined as the Euclidean distance between the transformed time-series data. Then, based the similarity between melodies of a music object, melodies are clustered and the representative of each cluster is extracted as one of theme melodies for the music. To construct the theme melody index, a theme melody is represented as a point of the multidimensional metric space of M-tree. For retrieval of user's query melody, the query melody is also transformed into a time-series data by the same way of indexing phase. To retrieve the similar melodies to the query melody given by user from the theme melody index the range query search algorithm is used. By the implementation of the prototype system using the proposed theme melody index we show the effectiveness of the proposed methods.

• Journal of Korea Multimedia Society
• /
• v.18 no.11
• /
• pp.1358-1366
• /
• 2015

This paper proposes an automatic composition method using the training capability of artificial neural networks and chord progression rules that are widely used by human composers. After training a given song, the new melody is generated by the trained artificial neural networks through applying a different initial melody to the neural networks. The generated melody should be modified to fit the rhythm and chord progression rules for generating natural melody. In order to achieve this object, we devised a post-processing method such as chord candidate generation, chord progression, and melody correction. From some tests we could find that the melody after the post-processing was very improved from the melody generated by artificial neural networks. This enables our composition system to generate a melody which is similar to those generated by human composers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.1 no.3
• /
• pp.77-82
• /
• 2008

In this paper, in the middle of progressing popular music chord, a method of inserting melody is addressed, which utilized by analyzing chord progress pattern. Firstly, a method for transforming melody into bit pattern which is to be used for neural network input is described. In order to insert the melody, composition pattern is learned from back propagation neural network, and based on these data new melody is to be generated. Experimental results verified the possibility of neural network based computer composition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.6038-6053
• /
• 2017

In this study, we propose an automatic melody extraction algorithm using deep learning. In this algorithm, feature images, generated using the energy of frequency band, are extracted from polyphonic audio files and a deep learning technique, a convolutional neural network (CNN), is applied on the feature images. In the training data, a short frame of polyphonic music is labeled as a musical note and a classifier based on CNN is learned in order to determine a pitch value of a short frame of audio signal. We want to build a novel structure of melody extraction, thus the proposed algorithm has a simple structure and instead of using various signal processing techniques for melody extraction, we use only a CNN to find a melody from a polyphonic audio. Despite of simple structure, the promising results are obtained in the experiments. Compared with state-of-the-art algorithms, the proposed algorithm did not give the best result, but comparable results were obtained and we believe they could be improved with the appropriate training data. In this paper, melody extraction and the proposed algorithm are introduced first, and the proposed algorithm is then further explained in detail. Finally, we present our experiment and the comparison of results follows.

• The KIPS Transactions:PartD
• /
• v.11D no.3
• /
• pp.495-508
• /
• 2004

Recently, in content-based music information retrieval systems, to enhance the response time of retrieving music data from large music database, some researches have adopted the indexing mechanism that extracts and indexes the representative melodies. The representative melody of music data must stand for the music itself and have strong possibility to use as users' input queries. However, since the previous researches have not considered the musical composition forms, they are not able to correctly catch the contrast, repetition and variation of motif in musical forms. In this paper, we use an index automatically constructed from representative melodies such like first melody, climax melodies and similarly repeated theme melodies. At first, we expand the clustering algorithm in order to extract similarly repeated theme melodies based on the musical composition forms. If the first melody and climax melodies are not included into the representative melodies of music by the clustering algorithm, we add them into representative melodies. We implemented a prototype system and did experiments on comparison the representative melody index with other melody indexes. Since, we are able to construct the representative melody index with the lower storage by 34％ than whole melody index, the response time can be decreased. Also, since we include first melody and climax melody which have the strong possibility to use as users' input query into representative melodies, we are able to get the more correct results against the various users' input queries than theme melody index with the cost of storage overhead of 20％.

• Journal of KIISE:Software and Applications
• /
• v.34 no.12
• /
• pp.1037-1044
• /
• 2007

Recently, we extract the representative melody of the music and index the music to reduce searching time at the content-based music retrieval system. The existing study has used MIDI data to extract a representative melody but it has a weak point that can use only MIDI data. Therefore, this paper proposes a representative melody retrieval method that can be use at all audio file format and uses digital signal processing. First, we use Fast Fourier Transform (FFT) and find the tempo and node for the representative melody retrieval. And we measure the frequency of high value that appears from PCM Data of each node. The point which the high value is gathering most is the starting point of a representative melody and an eight node from the starting point is a representative melody section of the audio data. To verity the performance of the method, we chose a thousand of the song and did the experiment to extract a representative melody from the song. In result, the accuracy of the extractive representative melody was 79.5% among the 737 songs which was found tempo.

• Journal of Biomedical Engineering Research
• /
• v.31 no.6
• /
• pp.417-426
• /
• 2010

We present a speech processing strategy incorporating instantaneous frequency (IF) encoding for the enhancement of melody recognition performance of cochlear implants. For the IF extraction from incoming sound, we propose the use of a Teager energy operator (TEO), which is advantageous for its lower computational load. From time-frequency analysis, we verified that the TEO-based method provides proper IF encoding of input sound, which is crucial for melody recognition. Similar benefit could be obtained also from the use of a Hilbert transform (HT), but much higher computational cost was required. The melody recognition performance of the proposed speech processing strategy was compared with those of a conventional strategy using envelope extraction, and the HT-based IF encoding. Hearing tests on normal subjects were performed using acoustic simulation and a musical contour identification task. Insignificant difference in melody recognition performance was observed between the TEO-based and HT-based IF encodings, and both were superior to the conventional strategy. However, the TEO-based strategy was advantageous considering that it was approximately 35% faster than the HT-based strategy.

• Journal of Korea Multimedia Society
• /
• v.8 no.1
• /
• pp.1-8
• /
• 2005

Similar melody searching is an operation that finds such melodies similar to a given query melody from a music database. In this paper, we address the development of a system that detects plagiarism based on the similar melody searching. We first Propose a novel similarity model that supports alignment as well as shifting. Also, we suggest a method for indexing the features extracted from each melody, and a method for processing plagiarism detection by using the index. By our plagiarism detection system composers can easily searches for such melodies that are similar to their ones from music databases. Through performance evaluation via a series of experiments, we show the effectiveness of our approach. The results reveal that our approach outperforms the sequential-scan-based one in speed up to around 31 times.

• Speech Sciences
• /
• v.4 no.2
• /
• pp.91-102
• /
• 1998

The present study attempted to modify the conventional Melodic Intonation Therapy (MIT) in three aspects: number of syllables of adjacent target utterances (ATU), melody patterns of ATU, and initial listening of melody and intoned speech with the eyes closed. The modified Melodic Intonation Therapy (MMIT) was applied to two severe Korean aphasics. The patients exhibited a severely nonfluent aphasia resulting from a left CVA(Cerebrovascular Accident). The purpose of the modification was to avoid perseveration and improve reflective listening skills. First, the treatment program avoided ATU with the same number of syllables. Second, four different patterns of melody were developed: rising type, falling type, V-type, and inverted V-type. One type of prosodic pattern was preceded and followed by another type of melody. These two variations were to decrease perseverative behaviors. Finally, the patients kept their eyes closed when the clinician played and hummed a target melody at the initial stage of the program in order to improve reflective listening skills. A single-subject alternating treatment design was used. The effects of MMIT were compared to the conventional MIT. Differing the number of syllables and the type of melodic patterns decreased perseverative behaviors and produced more correct names. The initial listening of the target melody with the patients' eyes closed seemed to increase their attentiveness and result in a more fluent production of target utterances. Probable reasons for the effectiveness of MMIT were discussed.

• The Journal of Korean Association of Computer Education
• /
• v.8 no.5
• /
• pp.109-118
• /
• 2005

In this paper, we present a music retrieval system that compares the geometric structure of a melody specified by a user with those in a music database. The system finds matches between a query melody and melodies in the database by analyzing both structural and contextual features. The retrieval method is based on the geometric hashing algorithm which consists of two steps; the preprocessing step and the recognition step. During the preprocessing step, we divide a melody into several fragments and analyze the pitch and duration of each note of the fragments to find a structural feature. To find a contextual feature, we find a main chord for each fragment. During the recognition step, we divide the query melody specified by a user into several fragments and search through all fragments in the database that are structurally and contextually similar to the melody. A vote is cast for each of the fragments and the music whose total votes are the maximum is the music that contains a matching melody against the query melody. Using our approach, we can find similar melodies in a music database quickly. We can also apply the method to detect plagiarism in music.