Abstract
Our work is within the framework of studying a sound analysis system in a telemedicine project. The task of this system is to detect situations of distress in a patient’s room basing on sound analysis. In this paper we present our studies on the constructions of a speech/non-speech discriminator and of a speech/scream-groan discriminator. The first discriminator’s task is to distinguish speech signal from non speech signal in a room such as sounds of broken glass, door shutting, chair falling, water in toilette, etc. The second one’s task is to detect sounds of scream-groan from speech signal. Results show that these discriminators are applicable to our sound analysis system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Istrate, D., Vacher, M., Castelli, E., Besacier, L., Sérignat, J.F.: Distress Situation Identification though Sound Processing. In: An Application to Medical Telemonitoring. European Conference on Computational Biology, Paris (2003)
Équipe GEOD Dan Istrate: C.-I. Base de données. Sons de la vie courante (2001)
Gauvain, J.L., Lamel, L.F., Eskenazi, M.: Design Considerations and Text Selection for BREF, a large French read-speech corpus. In: International Conference on Spoken Language Processing 1990, Kobe Japan (1990)
Saunders, J.: Real-Time Discrimination of Broadcast Speech/Music. In: International Conference on Acoustics, Speech and Signal Processing (1996)
Scheirer, E., Slaney, M.: Construction and Evaluation of a Robust Multifeature Music/Speech Discriminator. In: International Conference on Acoustics, Speech and Signal Processing (1997)
Carey, M.J., Parris, E.S., Lloyd-Thomas, H.: A Comparison of Features for Speech, Music Discrimination. In: International Conference on Acoustics, Speech and Signal Processing, Phoenix AZ (1999)
El-Maleh, K., Samouelian, A., Kabal, P.: Frame-Level Noise Classification in Mobile Environments. In: International Conference on Acoustics, Speech and Signal Processing, Phoenix AZ (1999)
Wegmann, S., Zhan, P., Gillick, L.: Progress in Broadcast News Transcription at Dragon Systems. In: International Conference on Acoustics, Speech and Signal Processing, Phoenix AZ, vol. I, pp. 33–36 (1999)
Moreno, P.J., Rifkin, R.: Using the Fisher Kernel Method for Web Audio Classification. In: International Conference on Acoustics, Speech and Signal Processing, vol. 4, pp. 2417–2420 (2000)
Lu, L., Zhang, H.-J., Jiang, H.: Content Analysis for Audio Classification and Segmentation. IEEE Transaction on speech and audio processing 10(7) (2002)
Ajmera, J., McCowan, I., Bourlard, H.: Speech/Music Segmentation Using Entropy and Dynamism Features in a HMM Classification Framework. Speech Communication 40, 351–363 (2003)
McKinney, M.F., Breebaart, J.: Features for Audio and Music Classification. In: 4th International Conference on Music Information, Maryland USA (2003)
Liu, M., Wang, C., Wang, L.P.: Content-Based Audio Classification and Retrieval Using a Fuzzy Logic System: Towards Multimedia Search Engines. Soft Computing 6, 357–364 (2002)
Schmandt, C., Vallejo, G.: “Listenin” to Domestic Environments from Remote Locations. In: International Conference on Auditory Display, Boston USA (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nguyen, C.P., Pham, T.N.Y., Eric, C. (2005). Toward a Sound Analysis System for Telemedicine. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_44
Download citation
DOI: https://doi.org/10.1007/11540007_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
eBook Packages: Computer ScienceComputer Science (R0)