A Dual Ternary Indexing Approach for Music Retrieval System

2008 ◽  
Vol 12 (3) ◽  
pp. 227-233
Author(s):  
Hewijin Christine Jiau ◽  
◽  
Chuan-Wang Chang
Keyword(s):  
Processing Time ◽  
Suffix Tree ◽  
Retrieval System ◽  
Response Times ◽  
Construction Process ◽  
Music Retrieval ◽  
Indexing Structure ◽  
Critical Issues ◽  
Music Information ◽  
And Storage

Memory usage for storing indexes and query response times for retrieval processing are two critical issues in music information retrieval (MIR) systems. In this paper, we propose an effective and efficient numeric indexing structure to overcome the difficulties of variable length queries and enhance the efficiency of music retrieval. The proposed structure differs greatly from pre-existing research in textual indexing techniques such asn-gram and suffix tree because it does not need to generate redundant and useless indexes. The index construction process has no complicated split and joint operations making, is easier and faster than tree-like methods. Experimental results show that our method is more scalable and economical than previous methods. The proposed method can significantly reduce the processing time and storage for retrieving and indexing.

scholarly journals Efficient Retrieval of Music Recordings Using Graph-Based Index Structures

Signals ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 336-352
Author(s):  
Frank Zalkow ◽  
Julian Brandner ◽  
Meinard Müller
Keyword(s):  
Nearest Neighbor ◽  
Response Times ◽  
Negative Impact ◽  
Nearest Neighbor Search ◽  
Index Structure ◽  
Search Problem ◽  
Index Structures ◽  
Music Retrieval ◽  
Retrieval Systems ◽  
Music Recordings

Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In this scenario, a fast response from the system is essential for a positive user experience. For realizing low response times, one requires index structures that facilitate efficient search operations. One such index structure is the K-d tree, which has already been used in music retrieval systems. As an alternative, we propose to use a modern graph-based index, denoted as Hierarchical Navigable Small World (HNSW) graph. As our main contribution, we explore its potential in the context of a cross-version music retrieval application. In particular, we report on systematic experiments comparing graph- and tree-based index structures in terms of the retrieval quality, disk space requirements, and runtimes. Despite the fact that the HNSW index provides only an approximate solution to the nearest neighbor search problem, we demonstrate that it has almost no negative impact on the retrieval quality in our application. As our main result, we show that the HNSW-based retrieval is several orders of magnitude faster. Furthermore, the graph structure also works well with high-dimensional index items, unlike the tree-based structure. Given these merits, we highlight the practical relevance of the HNSW graph for music information retrieval (MIR) applications.

MUSEMBLE: A novel music retrieval system with automatic voice query transcription and reformulation

2008 ◽  
Vol 81 (7) ◽  
pp. 1065-1080 ◽  
Author(s):  
Seungmin Rho ◽  
Byeong-jun Han ◽  
Eenjun Hwang ◽  
Minkoo Kim
Keyword(s):  
Retrieval System ◽  
Music Retrieval

scholarly journals Design and Analysis System of KNN and ID3 Algorithm for Music Classification based on Mood Feature Extraction

2017 ◽  
Vol 7 (1) ◽  
pp. 486
Author(s):  
Made Sudarma ◽  
I Gede Harsemadi
Keyword(s):  
Feature Extraction ◽  
Processing Time ◽  
Nearest Neighbor ◽  
Extraction Process ◽  
Performance Comparison ◽  
K Nearest Neighbor ◽  
K Value ◽  
Id3 Algorithm ◽  
Analysis System ◽  
Music Information

Each of music which has been created, has its own mood which is emitted, therefore, there has been many researches in Music Information Retrieval (MIR) field that has been done for recognition of mood to music.  This research produced software to classify music to the mood by using K-Nearest Neighbor and ID3 algorithm.  In this research accuracy performance comparison and measurement of average classification time is carried out which is obtained based on the value produced from music feature extraction process.  For music feature extraction process it uses 9 types of spectral analysis, consists of 400 practicing data and 400 testing data.  The system produced outcome as classification label of mood type those are contentment, exuberance, depression and anxious.  Classification by using algorithm of KNN is good enough that is 86.55% at k value = 3 and average processing time is 0.01021.  Whereas by using ID3 it results accuracy of 59.33% and average of processing time is 0.05091 second.

scholarly journals Clothed wax effigies: construction materials, challenges and suggestions for preventive conservation

2020 ◽  
Author(s):  
Christos Karydis ◽  
Evangelia Kyriazi ◽  
Christina-Alkisti Staka
Keyword(s):  
Environmental Conditions ◽  
Disaster Preparedness ◽  
Construction Materials ◽  
Construction Process ◽  
Preventive Conservation ◽  
Emergency Situations ◽  
And Storage

Wax effigies, fully dressed life-size models of human figures, have been constructed since the medieval times. The construction materials of historical effigies differ to the contemporary ones, yet the construction process of the wax parts has more or less remained unchanged over the centuries. This paper starts with the history, construction materials and manufacture techniques of wax effigies. The inseparable relation of the wax effigies and their costumes is explained, and the characteristics and deterioration agents of their most important construction materials are presented in order to understand their needs for preservation, with emphasis on wax and fabrics. The aim of this paper is to suggest preventive conservation guidelines for wax effigies, with proposals for appropriate environmental conditions during display and storage, and suggestions for proper handling, storage and transportation. Advice for disaster preparedness and actions in cases of emergency situations is also provided.

Relocation and Storage Assignment Strategies Evaluation in a Multiple-deep Tier-captive Automated Vehicles Storage and Retrieval System with Undetermined Retrieval Sequence

2021 ◽  
Author(s):  
Jakob Marolt ◽  
Nenad Kosanić ◽  
Tone Lerher
Keyword(s):  
Retrieval System ◽  
Discrete Event ◽  
Nearest Neighbour ◽  
Throughput Performance ◽  
Storage And Retrieval ◽  
Event Simulation ◽  
Retrieval Systems ◽  
Storage Assignment ◽  
And Storage

Abstract This paper studies multiple-deep automated vehicle storage and retrieval systems (AVS/RS) known for their high throughput performance and flexibility. Compared to a single-deep system, multiple-deep AVS/RS has a better space area utilisation. However, a relocation cycle occurs, reducing the throughput performance whenever another stock-keeping unit (SKU) blocks a retrieving SKU. The SKU retrieval sequence is undetermined, meaning that the arrangement is unknown, and all SKUs have an equal probability of retrieval. In addition to the shuttle carrier, a satellite vehicle is attached to the shuttle carrier and is used to access storage locations in multiple depths. A discrete event simulation of multiple-deep AVS/RS with a tier captive shuttle carrier was developed. We focused on the dual command cycle time assessment of nine different storage and relocation assignment strategies combinations in the simulation model. The results of a simulation study for (i) Random, (ii) Depth-first and (iii) Nearest neighbour storage and relocation assignment strategies combinations are examined and benchmarked for five different AVS/RS case study configurations with the same number of storage locations. The results display that the fivefold and sixfold deep AVS/RS outperform systems with fewer depths by utilising Depth-first storage and Nearest neighbour relocation assignment strategies.

Adaptive Indexing for Semantic Music Information Retrieval

2011 ◽  
pp. 287-300
Author(s):  
Clement H.C. Leung ◽  
Jiming Liu ◽  
Alfredo Milani ◽  
Alice W.S. Chan
Keyword(s):  
Information Retrieval ◽  
Music Information Retrieval ◽  
Research Area ◽  
Multimedia Databases ◽  
Music Retrieval ◽  
Digital Devices ◽  
Retrieval Systems ◽  
Music Information ◽  
High Level ◽  
Storage Technologies

With the rapid advancement of music compression and storage technologies, digital music can be easily created, shared and distributed, not only in computers, but also in numerous portable digital devices. Music often constitutes a key component in many multimedia databases, and as they grow in size and complexity, their meaningful search and retrieval become important and necessary. Music Information Retrieval (MIR) is a relatively young and challenging research area started since the late 1990s. Although some form of music retrieval is available on the Internet, these tend to be inflexible and have significant limitations. Currently, most of these music retrieval systems only rely on low-level music information contents (e.g., metadata, album title, lyrics, etc.), and in this chapter, the authors present an adaptive indexing approach to search and discover music information. Experimental results show that through such an indexing architecture, high-level music semantics may be incorporated into search strategies.

Design of an impression‐based music retrieval system

2006 ◽  
Vol 120 (5) ◽  
pp. 3236-3236
Author(s):  
Kimiko Ohta ◽  
Tadahiko Kumamoto ◽  
Hitoshi Isahara
Keyword(s):  
Retrieval System ◽  
Music Retrieval
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