In this paper we propose to use a state-of-the-art Deep Recurrent Neural Network (DRNN)
based Speech Enhancement (SE) algorithm for noise robust Speaker Verification (SV) …

The increasing need for secure authentication systems has motivated recent interest in
effective algorithms for Speaker Verification (SV). In particular, there is increasing need for …

Many spectrum estimation methods and speech enhancement algorithms have previously
been evaluated for noise-robust speaker identification (SID). However, these techniques …

We investigate the problem of speaker verification in noisy conditions in this paper. Our work
is motivated by the fact that environmental noise severely degrades the performance of …

The speech signal is a combination of attributes that contain information of the speaker,
channel and noise. Conventional speaker verification systems train a single generic model …

Acoustic model enhancement (AME) refers to adapting the acoustic models to compensate
for the distortion induced by a speech enhancement technique. This work extends the AME …

Aufgrund ihres individuellen, charakteristischen Klangs stellt die menschliche Stimme ein
biometrisches Merkmal dar, das zum Beispiel fur Anwendungen der Authentifizierung …

This thesis focuses on the robustness issues of speaker verification (SV) systems. Although
current SV systems perform well under clean condition, their performance degrades …

Speaker identification (SID) systems identify the speaker of a segment of speech and are
confounded by four factors:(i) variation in speaker characteristics over time,(ii) variation in …

Automatic speaker verification has many potential applications in security, surveillance and
access control. In many of these applications, it is necessary to verify the speaker based on …