Acoustic emotion recognition: A benchmark comparison of performances

Björn Schuller, Bogdan Vlasenko, Florian Eyben, Gerhard Rigoll, Andreas Wendemuth

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

223 Zitate (Scopus)

Abstract

In the light of the first challenge on emotion recognition from speech we provide the largest-to-date benchmark comparison under equal conditions on nine standard corpora in the field using the two pre-dominant paradigms: modeling on a frame-level by means of Hidden Markov Models and supra-segmental modeling by systematic feature brute-forcing. Investigated corpora are the ABC, AVIC, DES, EMO-DB, eNTERFACE, SAL, SmartKom, SUSAS, and VAM databases. To provide better comparability among sets, we additionally cluster each database's emotions into binary valence and arousal discrimination tasks. In the result large differences are found among corpora that mostly stem from naturalistic emotions and spontaneous speech vs. more prototypical events. Further, supra-segmental modeling proves significantly beneficial on average when several classes are addressed at a time.

OriginalspracheEnglisch
TitelProceedings of the 2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009
Seiten552-557
Seitenumfang6
DOIs
PublikationsstatusVeröffentlicht - 2009
Veranstaltung2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009 - Merano, Italien
Dauer: 13 Dez. 200917 Dez. 2009

Publikationsreihe

NameProceedings of the 2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009

Konferenz

Konferenz2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009
Land/GebietItalien
OrtMerano
Zeitraum13/12/0917/12/09

Fingerprint

Untersuchen Sie die Forschungsthemen von „Acoustic emotion recognition: A benchmark comparison of performances“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren