Speaker identification on compactRIO

Farjo, Joan; Aoun, M. Hamouche J.; Hamad, Mustapha; Kassem, Abdallah

doi:10.1109/melcon.2012.6196458

Cited by 3 publications

(1 citation statement)

References 7 publications

(9 reference statements)

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“…Speech recognition detects only the words, whereas the voice recognition disregards the language or anything linguistic for that matter and detects the identity of the person speaking [1]. Hence voice biometrics would use the voice recognition.…”

Section: Introductionmentioning

confidence: 99%

Android voice recognition application with multi speaker feature

Frewat

Baroud

Sammour

et al. 2016

2016 18th Mediterranean Electrotechnical Conference (MELECON)

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In this paper, we discuss two things. In the first part of the paper, we discuss the means of processing the speech signal using the Mel Frequency Cepstral Coefficients and the basics of voice characteristics. The problem of voice recognition was already implemented at the hardware level, but in this we propose a solution to the problem on the software end with a higher level of accuracy. Then in the second part, we will discuss the application developed on Android which is able to perform both single speaker and multi-speaker recognition. The multispeaker feature enables the system to identify more than one person speaking by splitting the input into smaller blocks and treating each block as a single speaker identification problem. In the single speaker recognition case, the algorithm is able to correctly identify the individual 90.3% of the time. In the multispeaker recognition case, up to 3 individuals are correctly identified roughly 86% of the time. The average identification time is 220ms across a database of 415 samples.

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Section: Introductionmentioning

confidence: 99%