Improving monaural speaker identification by double-talk detection

This paper describes a novel approach to improve monoaural speaker identification where two speakers are present in a single-microphone recording. The goal is to identify both of the underlying speakers in the given mixture. The proposed approach is composed of a double-talk detector (DTD) as a preprocessor and speaker identification back-end. We demonstrate that including the double-talk detector improves the speaker identification accuracy. Experiments on GRID corpus show that including the DTD improves average recognition accuracy from 96.53% to 97.43%.

• Type: Journal
• Year: 2010
• Where: INTERSPEECH
• Authors: Rahim Saeidi, Pejman Mowlaee, Tomi Kinnunen, Zheng-Hua Tan, Mads Græsbøll Christensen, Søren Holdt Jensen, Pasi Fränti
• Keywords: Double-talk Detector, INTERSPEECH 2010, Monoaural Speaker Identification, Signal Processing, Speaker Identification