Efficient speech edge detection for mobile health applications

• Published in: 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS) pp. 45 - 48
• Main Authors: Dingkun Du, Odame, K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2011
• Subjects: Bandwidth; Chirp; Encoding; Image edge detection; Sensors; Speech; Time frequency analysis
• ISBN: 9781457714696; 1457714698
• ISSN: 2163-4025; 2766-4465
• DOI: 10.1109/BioCAS.2011.6107723

Intelligent audio sensors that are continuously recording and analyzing sounds are a critical component of many emerging and future embedded applications. In these applications, the power budget is very tight, of which the analog front end consumes a major proportion. An efficient analog front end should adapt its power consumption to the instantaneous bandwidth of the audio signal of interest, instead of constantly consuming a fixed amount of power that assumes a fixed signal bandwidth. In this paper, we introduce a novel algorithm for identifying the edges of speech in the time-frequency domain, which is used to detect the instantaneous bandwidth of speech. A circuit implementation of our algorithm consumes 42.4μW of power and can extract the instantaneous bandwidth of a signal within an accuracy of 1% even in SNR conditions as low as 10 dB.