Closed-set Speaker Identification in Speech Gateways

It has been observed an ever increasing need to access information whenever and wherever you want, regardless the means by which it is achieved. A speech gateway proves to be an important tool to reduce the gap between information source and the individual. However, current implementations lack authentication modules for verifying the identity of system´s users, which is an enjoyable feature for a sort of applications. This paper presents the construction of a speaker identification module and its integration to VoiceXML-enabled speech gateways. Feature extraction has been made with Cepstrum and Vector Quantization has been used to perform properly recognition. Experiments have shown an accuracy rate of 87% in the identification of the speaker.