A conventional automatic speech recognizer does not perform well in the presence of noise, while human listeners are able to segregate and recognize speech in noisy conditions. We...
Yang Shao, Zhaozhang Jin, DeLiang Wang, Soundarara...
The popular mel-frequency cepstral coefficients (MFCCs) capture a mixture of speaker-related, phonemic and channel information. Speaker-related information could be further broke...
This paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real envir...
Audio segmentation is an essential preprocessing step in several audio processing applications with a significant impact e.g. on speech recognition performance. We introduce a no...
A half-duplex distributed beamforming technique for relay networks with frequency selective fading channels is developed. The network relays use the filter-and-forward (FF) strat...
Haihua Chen, Alex B. Gershman, Shahram Shahbazpana...
This paper proposes a new speech enhancement algorithm for the suppression of background noise and late reverberation without a priori knowledge. A generalized spectral weighting ...
We present an overview of the data collection and transcription efforts for the COnversational Speech In Noisy Environments (COSINE) corpus. The corpus is a set of multi-party con...
Alex Stupakov, Evan Hanusa, Jeff A. Bilmes, Dieter...
Distributed synchronization is known to occur at several scales in the brain, and has been suggested as playing a key functional role in perceptual grouping. State-of-the-art visu...
Least squares (LS) fitting is one of the most fundamental techniques in science and engineering. It is used to estimate parameters from multiple noisy observations. In many probl...