Uncertainty decoding for DNN-HMM hybrid systems based on numerical sampling

Hümmer C, Maas R, Schwarz A, Astudillo RF, Kellermann W (2015)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2015

Pages Range: 3556-3560

Event location: Dresden DE

ISBN: 978-1-5108-1790-6

Abstract

In this article, we propose an uncertainty decoding scheme for DNN-HMM hybrid systems based on numerical sampling. A finite set of samples is drawn from the estimated probability distribution of the acoustic features and subsequently passed through feature transformations/extensions and the deep neural network (DNN). Then, the nonlinearly-transformed feature samples are averaged at the output of the DNN in order to approximate the posterior distribution of the context-dependent Hidden Markov Model (HMM) states. This concept is experimentally verified for the REVERB challenge task using a reverberation-robust DNN-HMM hybrid system: The numerical sampling is performed in the logmelspec domain, where we estimate the posterior distribution of the acoustic features by combining coherence-based Wiener filtering and uncertainty propagation. The experimental results highlight the good performance of the proposed uncertainty decoding scheme with significantly increased recognition accuracy even for a small number of feature samples.

Authors with CRIS profile

Christian Hümmer Professur für Signalverarbeitung Roland Maas Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Andreas Schwarz Professur für Signalverarbeitung Walter Kellermann Professur für Signalverarbeitung

Involved external institutions

Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID) PT Portugal (PT)

How to cite

APA:

Hümmer, C., Maas, R., Schwarz, A., Astudillo, R.F., & Kellermann, W. (2015). Uncertainty decoding for DNN-HMM hybrid systems based on numerical sampling. In Proceedings of the Annual Conference of the International Speech Communication Association (Interspeech) (pp. 3556-3560). Dresden, DE.

MLA:

Hümmer, Christian, et al. "Uncertainty decoding for DNN-HMM hybrid systems based on numerical sampling." Proceedings of the Annual Conference of the International Speech Communication Association (Interspeech), Dresden 2015. 3556-3560.

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