Demo Data from EDBT 2026 / reviewers in the wild / expert
David Chamberlin
dblp:14/1498
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Audio and music processing · 70% Multimedia analysis and retrieval · 30% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval
audio retrieval |
0.0 | 1 | 1995 | Query by Humming: Musical Information Retrieval in an Audio Database · ACM Multimedia 1995 |
Audio and music processing
music information retrieval |
0.0 | 1 | 1995 | Query by Humming: Musical Information Retrieval in an Audio Database · ACM Multimedia 1995 |
Audio and music processing › music information retrieval › melody retrieval
query-by-humming |
0.0 | 1 | 1995 | Query by Humming: Musical Information Retrieval in an Audio Database · ACM Multimedia 1995 |
Audio and music processing › speech analysis
pitch tracking |
0.0 | 1 | 1995 | Query by Humming: Musical Information Retrieval in an Audio Database · ACM Multimedia 1995 |
Methods — techniques the papers use, named apart from their topics
relative pitch representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Query by Humming: Musical Information Retrieval in an Audio DatabaseabstractThe emergence of audio and video data types in databases will require new information retrieval methods adapted to the specific characteristics and needs of these data types. An effective and natural way of querying a musical audio database is by humming the tune of a song. In this paper, a system for querying an audio database by humming is described along with a scheme for representing the melodic information in a song as relative pitch changes. Relevant difficulties involved with tracking pitch are enumerated, along with the approach we followed, and the performance results of system indicating its effectiveness are presented. Asif Ghias, Jonathan Logan, David Chamberlin, Brian Christopher Smith |
ACM Multimedia | 3 |