Robust Vocal Intensity Prediction: Overcoming Dataset Bias with Pretrained Deep Models

Authors

Albert Rilliard (ORCID: https://orcid.org/0000-0001-6490-2386)
Marc Évrard (ORCID: https://orcid.org/0000-0002-6276-8141)
Jean-Sylvain Liénard
Quentin Le Tellier

Institutions

Laboratoire Interdisciplinaire des Sciences du Numérique (FR)

Publication Details

Published: 2025-08-17
DOI: https://doi.org/10.21437/interspeech.2025-2311
Primary Topic: Speech Recognition and Synthesis
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Robust Vocal Intensity Prediction: Overcoming Dataset Bias with Pretrained Deep Models

Albert Rilliard, Marc Évrard, Jean-Sylvain Liénard, Quentin Le Tellier

Aug 17, 2025

Speech Recognition and Synthesis

article

Robust Vocal Intensity Prediction: Overcoming Dataset Bias with Pretrained Deep Models

Albert Rilliard, Marc Évrard, Jean-Sylvain Liénard, Quentin Le Tellier

August 17, 2025article en

Abstract

No abstract available for this paper.

Laboratoire Interdisciplinaire des Sciences du Numérique (FR)

Openalex Percentile: Top 84%

Speech Recognition and Synthesis

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Robust Vocal Intensity Prediction: Overcoming Dataset Bias with Pretrained Deep Models — Albert Rilliard, Marc Évrard, et al. · (2025) | TGRS Research Map | TGRS