It is well known that MFCC based speaker identification (SID) systems easily break down under mismatched training and test conditions. One such mismatch occurs when a SID system ...
We present an algorithm for dereverberation of speech signals for automatic speech recognition (ASR) applications. Often ASR systems are presented with speech that has been record...
Kshitiz Kumar, Rita Singh, Bhiksha Raj, Richard M....
Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has receive...
This paper examines the performance of several source separation systems on a speech separation task for which human intelligibility has previously been measured. For anechoic mixt...
Michael I. Mandel, S. Bressler, Barbara G. Shinn-C...
The REMOS (REverberation MOdeling for Speech recognition) concept for reverberation-robust distant-talking speech recognition, introduced in [1] for melspectral features, is exten...
Hands-free devices are often used in a noisy and reverberant environment. Therefore, the received microphone signal does not only contain the desired near-end speech signal but als...
Emanuel A. P. Habets, Sharon Gannot, Israel Cohen,...
An audio recording is subject to a number of possible distortions and artifacts. For example, the persistence of sound, due to multiple reflections from various surfaces in a roo...
Current state-of-the-art speech recognition systems work quite well in controlled environments but their performance degrades severely in realistic acoustical conditions in reverb...
The length of the room impulse response characterizing the acoustic path between speaker and microphone is significantly larger than the length of the analysis window used for fea...
— Speech signals acquired in a reverberant room with microphones positioned at a distance from the talker are degraded in quality due to reverberation and measurement noise. Ther...
Nikolay D. Gaubitch, Emanuel A. P. Habets, Patrick...