---
_id: '11843'
abstract:
- lang: eng
text: Employing automatic speech recognition systems in hands-free communication
applications is accompanied by perfomance degradation due to background noise
and, in particular, due to reverberation. These two kinds of distortion alter
the shape of the feature vector trajectory extracted from the microphone signal
and consequently lead to a discrepancy between training and testing conditions
for the recognizer. In this chapter we present a feature enhancement approach
aiming at the joint compensation of noise and reverberation to improve the performance
by restoring the training conditions. For the enhancement we concentrate on the
logarithmic mel power spectral coefficients as features, which are computed at
an intermediate stage to obtain the widely used mel frequency cepstral coefficients.
The proposed technique is based on a Bayesian framework, to attempt to infer the
posterior distribution of the clean features given the observation of all past
corrupted features. It exploits information from a priori models describing the
dynamics of clean speech and noise-only feature vector trajectories as well as
from an observation model relating the reverberant noisy to the clean features.
The observation model relies on a simplified stochastic model of the room impulse
response (RIR) between the speaker and the microphone, having only two parameters,
namely RIR energy and reverberation time, which can be estimated from the captured
microphone signal. The performance of the proposed enhancement technique is finally
experimentally studied by means of recognition accuracy obtained for a connected
digits recognition task under different noise and reverberation conditions using
the Aurora~5 database.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Krueger A, Haeb-Umbach R. A Model-Based Approach to Joint Compensation of
Noise and Reverberation for Speech Recognition. In: Haeb-Umbach R, Kolossa D,
eds. Robust Speech Recognition of Uncertain or Missing Data. Springer;
2011.'
apa: Krueger, A., & Haeb-Umbach, R. (2011). A Model-Based Approach to Joint
Compensation of Noise and Reverberation for Speech Recognition. In R. Haeb-Umbach
& D. Kolossa (Eds.), Robust Speech Recognition of Uncertain or Missing
Data. Springer.
bibtex: '@inbook{Krueger_Haeb-Umbach_2011, title={A Model-Based Approach to Joint
Compensation of Noise and Reverberation for Speech Recognition}, booktitle={Robust
Speech Recognition of Uncertain or Missing Data}, publisher={Springer}, author={Krueger,
Alexander and Haeb-Umbach, Reinhold}, editor={Haeb-Umbach, Reinhold and Kolossa,
DorotheaEditors}, year={2011} }'
chicago: Krueger, Alexander, and Reinhold Haeb-Umbach. “A Model-Based Approach to
Joint Compensation of Noise and Reverberation for Speech Recognition.” In Robust
Speech Recognition of Uncertain or Missing Data, edited by Reinhold Haeb-Umbach
and Dorothea Kolossa. Springer, 2011.
ieee: A. Krueger and R. Haeb-Umbach, “A Model-Based Approach to Joint Compensation
of Noise and Reverberation for Speech Recognition,” in Robust Speech Recognition
of Uncertain or Missing Data, R. Haeb-Umbach and D. Kolossa, Eds. Springer,
2011.
mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “A Model-Based Approach to Joint
Compensation of Noise and Reverberation for Speech Recognition.” Robust Speech
Recognition of Uncertain or Missing Data, edited by Reinhold Haeb-Umbach and
Dorothea Kolossa, Springer, 2011.
short: 'A. Krueger, R. Haeb-Umbach, in: R. Haeb-Umbach, D. Kolossa (Eds.), Robust
Speech Recognition of Uncertain or Missing Data, Springer, 2011.'
date_created: 2019-07-12T05:29:20Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
editor:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
last_name: Haeb-Umbach
- first_name: Dorothea
full_name: Kolossa, Dorothea
last_name: Kolossa
language:
- iso: eng
publication: Robust Speech Recognition of Uncertain or Missing Data
publisher: Springer
status: public
title: A Model-Based Approach to Joint Compensation of Noise and Reverberation for
Speech Recognition
type: book_chapter
user_id: '44006'
year: '2011'
...