Summary of The Language Of Sound Search: Examining User Queries in Audio Search Engines, by Benno Weck and Frederic Font
The language of sound search: Examining User Queries in Audio Search Engines
by Benno Weck, Frederic Font
First submitted to arxiv on: 10 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Human-Computer Interaction (cs.HC); Information Retrieval (cs.IR); Machine Learning (cs.LG); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper investigates textual search queries in sound search engines, focusing on real-world user needs and behaviors. It analyzes two datasets: a custom survey and Freesound query logs, to understand how users formulate queries for unrestricted audio retrieval systems. The study reveals that survey queries are generally longer than Freesound queries, suggesting users prefer detailed queries when not limited by system constraints. Both datasets predominantly feature keyword-based queries, with few participants using full sentences. The findings highlight the importance of user-centered approaches in developing effective text-based audio retrieval systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how people search for sounds online. It talks about two ways to gather information: one is a special survey and the other is by looking at what people type into a website called Freesound. The study found that when people can search freely, they tend to ask more detailed questions. Most people use keywords to find what they’re looking for, not long sentences. This research will help make better tools for searching sounds online. |
