TY - GEN
T1 - Infrasonic scene fingerprinting for authenticating speaker location
AU - Aono, Kenji
AU - Chakrabartty, Shantanu
AU - Yamasaki, Toshihiko
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grant Nos. DGE-0802267 and DGE-1143954. K. Aono is an International Research Fellow of the Japan Society for the Promotion of Science (GR14001).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/16
Y1 - 2017/6/16
N2 - Ambient infrasound with frequency ranges well below 20 Hz is known to carry robust navigation cues that can be exploited to authenticate the location of a speaker. Unfortunately, many of the mobile devices like smartphones have been optimized to work in the human auditory range, thereby suppressing information in the infrasonic region. In this paper, we show that these ultra-low frequency cues can still be extracted from a standard smartphone recording by using acceleration-based cepstral features. To validate our claim, we have collected smartphone recordings from more than 30 different scenes and used the cues for scene fingerprinting. We report scene recognition rates in excess of 90% and a feature set analysis reveals the importance of the infrasonic signatures towards achieving the state-of-the-art recognition performance.
AB - Ambient infrasound with frequency ranges well below 20 Hz is known to carry robust navigation cues that can be exploited to authenticate the location of a speaker. Unfortunately, many of the mobile devices like smartphones have been optimized to work in the human auditory range, thereby suppressing information in the infrasonic region. In this paper, we show that these ultra-low frequency cues can still be extracted from a standard smartphone recording by using acceleration-based cepstral features. To validate our claim, we have collected smartphone recordings from more than 30 different scenes and used the cues for scene fingerprinting. We report scene recognition rates in excess of 90% and a feature set analysis reveals the importance of the infrasonic signatures towards achieving the state-of-the-art recognition performance.
KW - Acoustic Filtering
KW - Authentication
KW - Classifier
KW - Infrasound
KW - Localization
UR - http://www.scopus.com/inward/record.url?scp=85023749686&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2017.7952178
DO - 10.1109/ICASSP.2017.7952178
M3 - Conference contribution
AN - SCOPUS:85023749686
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 361
EP - 365
BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Y2 - 5 March 2017 through 9 March 2017
ER -