Kalle Palomäki

Academy Research Fellow, D.Sc.(Tech)
[ GROUP, PUBS ]

Contact Information

Office:

Room C314 in Computer Science Building,
Konemiehentie 2, Otaniemi campus area, Espoo

Mail address:

Aalto University School of Science,
Department of Information and Computer Science,
P.O. Box 15400, FI-00076 Aalto, Finland

Email:

kalle.palomaki (at) tkk.fi

Tel:

+358 9 470 25293

Fax:

+358 9 470 23277

Publications

Selected recent publications:
• Remes U., Palomäki K. J., Raiko T., Honkela A. and Kurimo M. (2011) Missing-feature reconstruction with bounded nonlinear state-space model, IEEE Signal processing letters, 18(10), 563-566. ieee-explore
• Palomäki K. J. and Brown G. J. (2011) A computational model of binaural speech recognition: role of across-frequency vs. within-frequency processing and internal noise, Speech Communication, 53(6), 924-940. science-direct.
• Pulakka H., Remes U., Yrttiaho S., Palomäki K., Kurimo M. and Alku P. (2011) Low-frequency bandwidth extension of telephone speech using sinusoidal synthesis and gaussian mixture model. In Proc. Interspeech 2011, Florence, Italy, Aug. 28-31, 2011. Winner of The ISCA Award for Best Student Paper.
• Kallasjoki H., Keronen S, Brown G. J., Gemmeke J. F., Remes U., and Palomäki K. J. (2011). Mask estimation and sparse imputation for missing data speech recognition in multisource reverberant environments. Proc. CHIME, pp. 58-63, Florence, Italy, September 2011.

For a full list, see my publications page.

Research

My main research interest is in noise robust automatic speech recognition. Particularly I am interested in models that are inspired by human auditory system, missing feature methods, binaural models and methods based on sparse representations. One of the specific application areas has been reverberation robust speech recognition. I am member of Speech Recognition Group and currently leading a noise robust team of three researchers: Ulpu Remes, Heikki Kallasjoki, and Sami Keronen . During my doctoral studies I have also conducted auditory brain research applying magnetoenchephalography.

Collaborators

Links to web pages of some recent collaborators and collaboration themes.
• Guy Brown: Auditory inspired models, binaural models and reverberant speech recognition
• Paavo Alku: Speech enhancement, noise robust features, and formerly MEG brain measurements
• Anthony Watkins: Auditory system inspired models for reverberant speech recognition
• Jon Barker: Recognition of reverberant speech
• Jort Gemmeke: Sparse representations and uncertainty modeling
• Tuomas Virtanen: Sparse separation and noise models
• Amy Beeston: Auditory system inspired models in reverberant speech recognition
• Hannu Pulakka: Speech bandwidth extension
• Jouni Pohjalainen: Noise robust feature extraction

Teaching

• T-61.6060 Noise robust speech recognition, spring 2009. Collection of articles written as course works.

Links

• Speech Recognition research group
• National Centre of Excellence in Adaptive Informatics