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Features for Content-Based Audio Retrieval - ScienceDirect
https://www.sciencedirect.com/science/article/pii/S0065245810780037#:~:text=3.1.%20Properties%20of%20Audio%20Features%20%20%20,%20Perceptual%2C%20physical%20%201%20more%20rows%20
Content-Based Audio Retrieval | SpringerLink
https://link.springer.com/chapter/10.1007/978-3-319-21945-5_7
J. P. B ello, Audio-based cover song retrieval using approximate chord sequences: testing shifts, gaps, swaps and beats, in Proceedings of the …
Content-Based Audio Retrieval | SR Subramanya and …
https://www.academia.edu/4728827/Content_Based_Audio_Retrieval
Summary and future directions We have presented a generalized algorithm for content-based audio retrieval using the concept of a "virtual-node." The algorithm is an improvement over our previous "partial-matching" algorithm and also exploits the multiresolution data structure of the unified k-tree model.
Features for Content-Based Audio Retrieval
https://publik.tuwien.ac.at/files/PubDat_186351.pdf
Content-based audio retrieval is an ill-posed problem (also known as inverse problem). In general, an ill-posed problem is concerned with the estimation of model parameters by the manipulation of observed data. In case of a retrieval task, model parameters are terms, properties and concepts that may represent 4.
Features for Content-Based Audio Retrieval - ScienceDirect
https://www.sciencedirect.com/science/article/pii/S0065245810780037
Content Based Audio Retrieval using Chord
https://www.ijedr.org/papers/IJEDR1702249.pdf
concept is based on the content of a given audio document and extracting the necessary information from it. The proposed content based audio retrieval system retrieves relevant songs from a large dataset of music audio tracks based on melody similarity. Relevant song retrieval is done by recognizing and extracting chord progressions (CPs).
Features for Content-Based Audio Retrieval - ScienceDirect
https://www.sciencedirect.com/science/article/abs/pii/S0065245810780037
Abstract. Today, a large number of audio features exists in audio retrieval for different purposes, such as automatic speech recognition, music information retrieval, audio segmentation, and environmental sound retrieval. The goal of this chapter is to review latest research in the context of audio feature extraction and to give an application-independent overview of the most …
[PDF] Features for Content-Based Audio Retrieval ...
https://www.semanticscholar.org/paper/Features-for-Content-Based-Audio-Retrieval-Mitrovic-Zeppelzauer/382dba7d6c645d55ebe9ef6735d502521f3b33dc
Content Based Audio Retrieval system is very helpful to facilitate users to find the target audio materials. Audio signals are classified into speech, music, …
(PDF) Features for Content-Based Audio Retrieval.
https://www.researchgate.net/publication/220662548_Features_for_Content-Based_Audio_Retrieval
A content-based (audio) retriev al system consists of multiple parts, illustrated in Figure 1. There are three modules: the input mo dule, the query module, and the
A TEXT RETRIEVAL APPROACH TO CONTENT-BASED AUDIO …
http://www.ideal.ece.utexas.edu/pdfs/164.pdf
This paper presents a novel approach to robust, content-based retrieval of digital music. We formulate the hash-ing and retrieval problems analogously to that of text re-trieval and leverage established results for this unique ap-plication. Accordingly, songs are represented as a ”Bag-of-Audio-Words” and similarity calculations follow directly
Content-Based Audio Classification and Retrieval Using ...
https://link.springer.com/chapter/10.1007/978-981-13-6861-5_23
The application areas of audio classification and retrieval system include speaker recognition, gender classification, music genre classification, environment sound classification, etc. This paper proposes a machine learning- and neural network-based approach which performs audio pre-processing, segmentation, feature extraction, classification and retrieval of audio …
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