When the Music Stops: Tip-of-the-Tongue Retrieval for Music

Samarth Bhargav and Anne Schuth and Claudia Hauff. In Proceedings of SIGIR'23, 2023.
8 citations

Abstract

We present the first study of Tip-of-the-tongue (ToT) retrieval for music, where a searcher is trying to find an existing music entity, but is unable to succeed as they cannot accurately recall important identifying information. ToT information needs are characterized by complexity, verbosity, uncertainty, and possible false memories. We make four contributions. (1) We collect a dataset—ToT𝑀𝑢𝑠𝑖𝑐 —of 2,278 information needs and ground truth answers. (2) We introduce a schema for these information needs and show that they often involve multiple modalities encompassing several Music IR sub- tasks such as lyric search, audio-based search, audio fingerprinting, and text search. (3) We underscore the difficulty of this task by benchmarking a standard text retrieval approach on this dataset. (4) We investigate the efficacy of query reformulations generated by a large language model ( LLM), and show that they are not as effective as simply employing the entire information need as a query–leaving a lot of open questions for future research.

Links

When the Music Stops: Tip-of-the-Tongue Retrieval for Music
https://github.com/spotify-research/tot
https://arxiv.org/abs/2305.14072
https://doi.org/10.1145/3539618.3592086
Google Scholar

Supervised Student

Samarth Bhargav
PhD Student at the University of Amsterdam, 2022-2023

Bib

@inproceedings{bhargav2023,
  title = {When the Music Stops: Tip-of-the-Tongue Retrieval for Music},
  author = {Samarth Bhargav and Anne Schuth and Claudia Hauff},
  year = {2023},
  booktitle = {Proceedings of SIGIR'23},
  doi = {10.1145/3539618.3592086}
}