Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices

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Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices. / Drossos, Konstantinos; Kotsakis, Rigas; Pappas, Panos; Kalliris, George; Floros, Andreas.

Audio Engineering Society Convention 134. AES Audio Engineering Society, 2013. 8812.

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Harvard

Drossos, K, Kotsakis, R, Pappas, P, Kalliris, G & Floros, A 2013, Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices. julkaisussa Audio Engineering Society Convention 134., 8812, AES Audio Engineering Society.

APA

Drossos, K., Kotsakis, R., Pappas, P., Kalliris, G., & Floros, A. (2013). Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices. teoksessa Audio Engineering Society Convention 134 [8812] AES Audio Engineering Society.

Vancouver

Drossos K, Kotsakis R, Pappas P, Kalliris G, Floros A. Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices. julkaisussa Audio Engineering Society Convention 134. AES Audio Engineering Society. 2013. 8812

Author

Drossos, Konstantinos ; Kotsakis, Rigas ; Pappas, Panos ; Kalliris, George ; Floros, Andreas. / Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices. Audio Engineering Society Convention 134. AES Audio Engineering Society, 2013.

Bibtex - Lataa

@inproceedings{27e667fa65e44bfa8ca46296754d26b7,

title = "Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices",

abstract = "Many common consumer devices use a short sound indication for declaring various modes of their functionality, such as the start and the end of their operation. This is likely to result in an intuitive auditory human-machine interaction, imputing a semantic content to the sounds used. In this paper we investigate sound patterns mapped to {"}Start{"} and {"}End{"} of operation manifestations and explore the possibility such semantics’ perception to be based either on users’ prior auditory training or on sound patterns that naturally convey appropriate information. To this aim, listening and machine learning tests were conducted. The obtained results indicate a strong relation between acoustic cues and semantics along with no need of prior knowledge for message conveyance.",

author = "Konstantinos Drossos and Rigas Kotsakis and Panos Pappas and George Kalliris and Andreas Floros",

year = "2013",

month = "5",

language = "English",

booktitle = "Audio Engineering Society Convention 134",

publisher = "AES Audio Engineering Society",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Investigating Auditory Human-Machine Interaction: Analysis and Classification of Sounds Commonly Used by Consumer Devices

AU - Drossos, Konstantinos

AU - Kotsakis, Rigas

AU - Pappas, Panos

AU - Kalliris, George

AU - Floros, Andreas

PY - 2013/5

Y1 - 2013/5

N2 - Many common consumer devices use a short sound indication for declaring various modes of their functionality, such as the start and the end of their operation. This is likely to result in an intuitive auditory human-machine interaction, imputing a semantic content to the sounds used. In this paper we investigate sound patterns mapped to "Start" and "End" of operation manifestations and explore the possibility such semantics’ perception to be based either on users’ prior auditory training or on sound patterns that naturally convey appropriate information. To this aim, listening and machine learning tests were conducted. The obtained results indicate a strong relation between acoustic cues and semantics along with no need of prior knowledge for message conveyance.

AB - Many common consumer devices use a short sound indication for declaring various modes of their functionality, such as the start and the end of their operation. This is likely to result in an intuitive auditory human-machine interaction, imputing a semantic content to the sounds used. In this paper we investigate sound patterns mapped to "Start" and "End" of operation manifestations and explore the possibility such semantics’ perception to be based either on users’ prior auditory training or on sound patterns that naturally convey appropriate information. To this aim, listening and machine learning tests were conducted. The obtained results indicate a strong relation between acoustic cues and semantics along with no need of prior knowledge for message conveyance.

M3 - Conference contribution

BT - Audio Engineering Society Convention 134

PB - AES Audio Engineering Society

ER -

TUTCRIS