Identifying a person by his or her voice is an important human trait most take for granted in
natural human-to-human interaction/communication. Speaking to someone over the …

Speaker recognition has emerged as an important field over the past several decades and
has evolved over time. This work is attempted to investigate speaker verification (SV) …

Research in speaker recognition has recently seen significant progress due to the
application of neural network models and the availability of new large-scale datasets. There …

In the context of the Internet age, the tourism industry has opened up new development
opportunities with the help of Internet technology advancement. It has produced many …

In real-world environments, noisy utterances with variable noise levels are recorded and
then converted to i-vectors for cosine distance or PLDA scoring. This paper investigates the …

While i-vector/PLDA framework has achieved great success, its performance still degrades
dramatically under noisy conditions. To compensate for the variability of i-vectors caused by …

The mismatch between enrollment and test utterances due to different types of variabilities is
a great challenge in speaker verification. Based on the observation that the SNR-level …

A linear predictive spectral estimation method based on higher-lag autocorrelation
coefficients is proposed for the noise-robust feature extraction from speech. The method …

The data dependence due to multiple use of the same subjects has impact on the standard
error (SE) of the detection cost function (DCF) in speaker recognition evaluation. The DCF is …

We present a study examining feature selection from high performing models evolved using
genetic programming (GP) on the problem of automatic speaker verification (ASV). ASV is a …