Utterance Based Speaker Identification Using ANN

Utterance Based Speaker Identification Using Ann

In this paper we present the implementation of speaker identification system using artificial neural network with digital signal processing. The system is designed to work with the text-dependent speaker identification for Bangla Speech. The utterances of speakers are recorded for specific Bangla words using an audio wave recorder. The speech features are acquired by the digital signal processi...

Improving short utterance based i-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance-duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations ...

Rapid unsupervised speaker adaptation using single utterance based on MLLR and speaker selection

In this paper, we employ the concept of HMM-Sufficient Statistics (HMM-Suff Stat) and N-best speakers selection to realize a rapid implementation of Baum-Welch and MLLR. Only a single arbitrary utterance is required which is used to select the N-best speakers HMM-Suff Stat from the training database as adaptation data. Since HMM-Suff Stat are pre-computed offline, computation load is minimized....

Modified Technique for Speaker Recognition using ANN

Speaker recognition consists of three phases: pre-processing, feature extraction and classification. During the first phase, the computer records the voice pattern of the speaker and analyse it. By the end of the second phase, the main features of the voice pattern are extracted. In the third phase, many classification techniques are exist such as artificial neural network (ANN) , hidden Markov...

User Customized HMM/ANN-based Speaker Verification