The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Incorporating user characteristics and contextual information has shown to be essential when it comes to personalized music retrieval and recommendation. To this end, the current location of a user is often exploited. However, relying solely on GPS coordinates neglects the cultural background of users, which does not necessarily coincide with political borders. In this paper, we analyze culture-specific...
We introduce Kara1k, a new musical dataset composed of 2,000 analyzed songs thanks to a partnership with a karaoke company. The dataset is divided into 1,000 cover songs provided by Recisio Karafun application1, and the corresponding 1,000 songs by the original artists. Kara1k is mainly dedicated toward cover song identification and singing voice analysis. For both tasks, it offers novel approaches,...
Identification of music components and further acoustic analysis of Indian classical music are challenging issues, due to large variations in these. This papers consists of two major studies, singing-voice analysis and music-source separation. Indian ragas are divided into lyrical composition and alaap regions, i.e., regions of improvisation that indicate versatility of the singer. Acoustic analyses...
A novel method to construct a network based on heterogeneous features obtained from music videos and social metadata for music video recommendation is presented in this paper. The proposed method enables construction of the network that can accurately associate users with music videos corresponding to their preference by the collaborative use of audio and textual features obtained from music videos...
Musical instruments are consist of wide variety of domain so manual classification of these instruments is difficult and challenging task. To make the process of classifying musical instrument easy and less dependent on human supervision given system is designed. There are some algorithm are available for classification tsk from which we uses SVM, MLP and AdaBoost for better result. This system mainly...
İn this study, we aim at gathering more scientific information about the musical data by using computer techology, and we are willing, to some extent, figure out the maqam structure of Traditional Turkish Art Music interpreted in the compositions. For this reason, 120 compositions from among Muhayyer Kurdi, Acem Kurdi and Kurdi makams in Traditional Turkish Art Music have been analysed and these compositions...
We present an end-to-end system for musical key estimation, based on a convolutional neural network. The proposed system not only out-performs existing key estimation methods proposed in the academic literature; it is also capable of learning a unified model for diverse musical genres that performs comparably to existing systems specialised for specific genres. Our experiments confirm that different...
Users of video-sharing sites often search for derivative works of music, such as live versions, covers, and remixes. Audio and video content are both important for retrieval: “karaoke” specifies audio content (instrumental version) and video content (animated lyrics). Although YouTube's text search is fairly reliable, many search results do not match the exact query. We introduce an algorithm to classify...
Automatic analysis of the mood of a piece of music is of great value in music searching, understanding, recommendation and some other music-related applications. Different from most of previous methods that adopted a discriminative mood classification scheme, in this paper, we propose a generative multimodal method for automatically classifying the mood of a piece of music based on effective learning...
The key to a recommendation system is the prediction of users' preferences. Personalized recommendation for many online music applications depends on the prediction of both long-term as well as the short-term preferences. In this paper, we propose a novel personalized next-song recommendation system that jointly consider the long-term and short-term preferences in its design. To depict the long-term...
Automated musical genre classification using machine learning techniques has gained popularity for research and development of powerful tools to organize music collections available on web. Mel cepstral co-efficients (MFCC's) have been successfully used in music genre classification but they do not reflect the correlation between the adjacent co-efficients of Mel filters of a frame neither the relation...
A novel method of automatic music genre classification based on the fusion of features is proposed. The features derived from the predominant melodic contour are combined with Modified Group Delay Features (MODGDF) in the front-end. Support vector machine (SVM) classifier is used for the classification of excerpts into five different musical genres. A baseline system using Mel-Frequency Cepstral Coefficients...
In this paper, we discuss the multipitch streaming (MPS) problem for a multi-source audio signal having interweaving pitch contours. We propose two approaches to tackle this challenge, one relates to a feature extracted from the energy levels distributed in multi-channel recordings for better characterization of the source, and the other uses particle swarm optimization (PSO) to enlarge the search...
In this paper we focus on the characterization of singing styles in world music. We develop a set of contour features capturing pitch structure and melodic embellishments. Using these features we train a binary classifier to distinguish vocal from non-vocal contours and learn a dictionary of singing style elements. Each contour is mapped to the dictionary elements and each recording is summarized...
In this paper, we propose a set of audio features to describe the quality of an audio signal. Audio quality is here considered as being modified by the chain of processes/effects applied to the individual instrument tracks to obtain the final mix of a musical piece. Thus, the quality also depends on the mastering processes applied to the final mix or the signal degradation caused by MP3 compression...
Metric learning for music is an important problem for many music information retrieval (MIR) applications such as music generation, analysis, retrieval, classification and recommendation. Traditional music metrics are mostly defined on linear transformations of handcrafted audio features, and may be improper in many situations given the large variety of music styles and instrumentations. In this paper,...
This paper presents a study about estimating the emotions conveyed in clips of background music (BGM) to be used in an automatic slideshow creation system. The system we aimed to develop, automatically tags each given pieces of background music with the main emotion it conveys, in order to recommend the most suitable music clip to the slideshow creators, based on the main emotions of embedded photos...
In this paper, we introduce a synchronization method of music and video, where the music is arranged with the video using emotion similarity. The music segments are matched with the video segments so that the music best follows the video's narrative. The temporal order of video segments are unchanged. Due to the disparity of structural musical content between segment boundaries, we design a cost function...
In this paper, we propose a music management framework to manage the distribution of large volume music contents at home and abroad. In this paper, we define the music contents as an expression model that can be distributed internationally, and distribute the sound sources, analyze all the transaction information and related tasks of the distributed music, process them into various types of data....
Most of the previous approaches to lyrics-to-audio alignment used a pre-developed automatic speech recognition (ASR) system that innately suffered from several difficulties to adapt the speech model to individual singers. A significant aspect missing in previous works is the self-learnability of repetitive vowel patterns in the singing voice, where the vowel part used is more consistent than the consonant...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.