INVESTIGADORES
FERRER Luciana
congresos y reuniones científicas
Título:
A Unified Approach for Audio Characterization and its Application to Speaker Recognition
Autor/es:
L. FERRER; L. BURGET; O. PLCHOT; N. SCHEFFER
Reunión:
Workshop; Proc. Odyssey Speaker and Language Recognition Workshop; 2012
Institución organizadora:
International Speech Communication Association
Resumen:
Systems designed to solve speech processing tasks like speech
or speaker recognition, language identification, or emotion detection are known to be affected by the recording conditions
of
the acoustic signal, like the channel, background noise, rever
beration, and so on. Knowledge of the nuisance characteristics
present in the signal can be used to improve performance of the
system. In some cases, the nature of these nuisance characteristics is known a priori, but in most practical cases it is not. Most
approaches used to automatically detect the characteristics of a
signal are designed for a specific type of effect: noise, reverberation, language, type of channel, and so on. We propose
a method for detecting the audio characteristics of a signal
in a unified way, based on iVectors. We show results for the detect
or
itself and for its use as metadata during calibration of a state-of-the-art speaker recognition system based on iVectors extracted
from Mel frequency cepstral coefficients. Results show relative
gains in equal error rate of up to 15% in a variety of recordingconditions.