Speech enhancement has substantial interest in the utilization of speaker identification,
video-conference, speech transmission through communication channels, speech-based …

This paper presents a new feature extraction algorithm called power normalized Cepstral
coefficients (PNCC) that is motivated by auditory processing. Major new features of PNCC …

From the available biometric technologies, automatic speaker recognition is one of the most
convenient and accessible ones due to abundance of mobile devices equipped with a …

Spoken term discovery is the task of automatically identifying words and phrases in speech
data by searching for long repeated acoustic patterns. Initial solutions relied on exhaustive …

Mel-frequency cepstral coefficients (MFCC) have been dominantly used in speaker
recognition as well as in speech recognition. However, based on theories in speech …

Acoustic front-ends are typically developed for supervised learning tasks and are thus
optimized to minimize word error rate, phone error rate, etc. However, in recent efforts to …

This paper examines the individual and combined impacts of various front-end approaches
on the performance of deep neural network (DNN) based speech recognition systems in …

The language identification (LID) task in the Robust Automatic Transcription of Speech
(RATS) program is challenging due to the noisy nature of the audio data collected over …

The task of query-by-example spoken term detection (QbE-STD) is to find a spoken query
within spoken audio data. Current state-of-the-art techniques assume zero prior knowledge …

Speech applications in far-field real world settings often deal with signals that are corrupted
by reverberation. The task of dereverberation constitutes an important step to improve the …