Hybrid Query by Humming and Metadata Search System (HQMS) Analysis over Diverse Features

Retrieval of music content over web is one of the toughest job tasks and found some of the significant challenge. Song retrieval over web is the emerging problem from the category of Music Information Retrieval. Several searching techniques related to metadata and content of song are developed and implemented. In this paper we are going to propose and evaluate a new hybrid technique for song retrieval named as “hybrid query by humming and metadata search system” (HQMS).HQMS is a hybrid model that is based on metadata and query by humming. HQMS narrow downs the relevant results thus improve overall accuracy of the system. Two filters, metadata and query by humming work together and enhances overall accuracy. The system is evaluated song wise, metadata wise and Age wise. Issues related to query reformulation are also highlighted as a part of the paper. More over the evaluation validates the hypothesis and the proposed Architecture.

@article{Khan2011,
  title     = {Hybrid Query by Humming and Metadata Search System (HQMS) Analysis over Diverse Features},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {2},
  number    = {9},
  year      = {2011},
  publisher = {The Science and Information Organization},
  author    = {Nauman Ali Khan and Mubashar Mushtaq},
  doi       = {10.14569/IJACSA.2011.020911},
  url       = {https://doi.org/10.14569/IJACSA.2011.020911}
}