Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

K. I. Nordstrom

dblp:26/5732 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Audio and music processing
linear prediction
0.112008
Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction · IEEE Trans. Speech Audio Process. 2008
Audio and music processing
speech analysis
0.112008
Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction · IEEE Trans. Speech Audio Process. 2008
Audio and music processing
voice conversion
0.112008
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
YearPublicationVenuePosition
2008 Transforming Perceived Vocal Effort and Breathiness Using Adaptive Pre-Emphasis Linear Prediction
abstract
This 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