{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/iiit-h-system-for-mediaeval-2014-quesst","title":"IIIT-H System for MediaEval 2014 QUESST","arxiv_id":null,"date":"2014-10-16","proceeding":null,"authors":["Santosh Kesiraju","Gautam Mantena","Kishore Prahallad"],"abstract":"This paper describes the experiments and observations for Query-by-Example Search on Speech Task (QUESST) at MediaEval 2014. In this paper, we describe two different representations of speech that were explored for the task. We also show the capabilities and limitations of non-segmental dynamic time warping (NS-DTW) technique for searching various types of queries. This paper mainly focuses on the experiments and analysis of the existing NS-DTW algorithm for various types of queries. The observations show that for a specific representation of speech, the algorithm is capable of detecting partial matches","url_abs":"https://www.researchgate.net/publication/292846899_IIIT-H_system_for_mediaeval_2014_Quesst","url_pdf":"https://www.researchgate.net/publication/292846899_IIIT-H_system_for_mediaeval_2014_Quesst","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"dynamic-time-warping","task_name":"Dynamic Time Warping"},{"task_slug":"keyword-spotting","task_name":"Keyword Spotting"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/keyword-spotting-on-quesst","task":"Keyword Spotting","dataset":"QUESST","model":"NS-DTW(for the development set, all the queries)","rank_in_archive_order":29,"of":69,"metrics":{"ATWV":"0.2261","Cnxe":"0.9121","MTWV":"0.2263","MinCnxe":"0.8070"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}