Demo Data from VLDB 2026 / reviewers in the wild / expert
K. I. Nordstrom
dblp:26/5732
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author
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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing
linear prediction |
0.1 | 1 | 2008 | Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction · IEEE Trans. Speech Audio Process. 2008 |
Audio and music processing
speech analysis |
0.1 | 1 | 2008 | Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction · IEEE Trans. Speech Audio Process. 2008 |
Audio and music processing
voice conversion |
0.1 | 1 | 2008 | Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction · IEEE Trans. Speech Audio Process. 2008 |
Methods — techniques the papers use, named apart from their topics
listening experiment · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear PredictionabstractThis paper presents a technique to transform high-effort voices into breathy voices using adaptive pre-emphasis linear prediction (APLP). The primary benefit of this technique is that it estimates a spectral emphasis filter that can be used to manipulate the perceived vocal effort. The other benefit of APLP is that it estimates a formant filter that is more consistent across varying voice qualities. This paper describes how constant pre-emphasis linear prediction (LP) estimates a voice source with a constant spectral envelope even though the spectral envelope of the true voice source varies over time. A listening experiment demonstrates how differences in vocal effort and breathiness are audible in the formant filter estimated by constant pre-emphasis LP. APLP is presented as a technique to estimate a spectral emphasis filter that captures the combined influence of the glottal source and the vocal tract upon the spectral envelope of the voice. A final listening experiment demonstrates how APLP can be used to effectively transform high-effort voices into breathy voices. The techniques presented here are relevant to researchers in voice conversion, voice quality, singing, and emotion. K. I. Nordstrom, George Tzanetakis, Peter F. Driessen |
IEEE Trans. Speech Audio Process. | 1 |