A hybrid approach to speaker recognition in multi-speaker environment

Recognition of voice in a multi-speaker environment involves speech separation, speech feature extraction and speech feature matching. Though traditionally vector quantization is one of the algorithms used for speaker recognition; its effectiveness is not well appreciated in case of noisy or multi-speaker environment. This paper describes the usability of the Independent Component Analysis (ICA) technique to enhance the effectiveness of speaker recognition using vector quantization. Results obtained by this approach are compared with that obtained using a more direct approach to establish the usefulness of the proposed method.