Learning new acoustic events in an HMM-based system using MAP adaptation

Jürgen T. Geiger; Mohamed Anouar Lakhal; Björn Schuller; Gerhard Rigoll

Learning new acoustic events in an HMM-based system using MAP adaptation

Jürgen T. Geiger
, Mohamed Anouar Lakhal
, Björn Schuller
, Gerhard Rigoll

Technical University of Munich

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

In this paper, we present a system for the recognition of acoustic events suited for a robotic application. HMMs are used to model different acoustic event classes. We are especially looking at the open-set case, where a class of acoustic events occurs that was not included in the training phase. It is evaluated how newly occuring classes can be learnt using MAP adaptation or conventional training methods. A small database of acoustic events was recorded with a robotic platform to perform the experiments.

Original language	English
Pages (from-to)	293-296
Number of pages	4
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
State	Published - 2011
Event	12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: 27 Aug 2011 → 31 Aug 2011

Keywords

Acoustic event classification
Hidden Markov models
Model adaptation

Cite this

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title = "Learning new acoustic events in an HMM-based system using MAP adaptation",

abstract = "In this paper, we present a system for the recognition of acoustic events suited for a robotic application. HMMs are used to model different acoustic event classes. We are especially looking at the open-set case, where a class of acoustic events occurs that was not included in the training phase. It is evaluated how newly occuring classes can be learnt using MAP adaptation or conventional training methods. A small database of acoustic events was recorded with a robotic platform to perform the experiments.",

keywords = "Acoustic event classification, Hidden Markov models, Model adaptation",

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year = "2011",

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journal = "Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",

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T1 - Learning new acoustic events in an HMM-based system using MAP adaptation

AU - Geiger, Jürgen T.

AU - Lakhal, Mohamed Anouar

AU - Schuller, Björn

AU - Rigoll, Gerhard

PY - 2011

Y1 - 2011

N2 - In this paper, we present a system for the recognition of acoustic events suited for a robotic application. HMMs are used to model different acoustic event classes. We are especially looking at the open-set case, where a class of acoustic events occurs that was not included in the training phase. It is evaluated how newly occuring classes can be learnt using MAP adaptation or conventional training methods. A small database of acoustic events was recorded with a robotic platform to perform the experiments.

AB - In this paper, we present a system for the recognition of acoustic events suited for a robotic application. HMMs are used to model different acoustic event classes. We are especially looking at the open-set case, where a class of acoustic events occurs that was not included in the training phase. It is evaluated how newly occuring classes can be learnt using MAP adaptation or conventional training methods. A small database of acoustic events was recorded with a robotic platform to perform the experiments.

KW - Acoustic event classification

KW - Hidden Markov models

KW - Model adaptation

UR - https://www.scopus.com/pages/publications/84865767330

M3 - Conference article

AN - SCOPUS:84865767330

SN - 2308-457X

SP - 293

EP - 296

JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

T2 - 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011

Y2 - 27 August 2011 through 31 August 2011

ER -

Learning new acoustic events in an HMM-based system using MAP adaptation

Abstract

Keywords

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