A CNN based Speaker Recognition System using an Alternate Bone Microphone
Khadar Nawas K1, A Nayeemulla Khan2

1NKhadar Nawas K*, SCSE, Vellore Institute of Technology, Chennai, India.
2A Nayeemulla Khan, SCSE, Vellore Institute of Technology , Chennai, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 4224-4227 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7647129219/2019©BEIESP | DOI: 10.35940/ijitee.B7647.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: State-of-art speaker recognition system uses acoustic microphone speech to identify/verify a speaker. The multimodal speaker recognition system includes modality of input data recorded using sources like acoustics mic,array mic ,throat mic, bone mic and video recorder. In this paper we implemented a multi-modal speaker identification system with three modality of speech as input, recorded from different microphones like air mic, throat mic and bone mic . we propose and claim an alternate way of recording the bone speech using a throat microphone and the results of a implemented speaker recognition using CNN and spectrogram is presented. The obtained results supports our claim to use the throat microphone as suitable mic to record the bone conducted speech and the accuracy of the speaker recognition system with signal speech recorded from air microphone get improved about 10% after including the other modality of speech like throat and bone speech along with the air conducted speech. 
Keywords: Throat Speech, Bone Speech, Speaker Identification, CNN, Multi-modal Speaker Recognition.
Scope of the Article: Pattern Recognition