A corpus-based approach to speech enhancement from nonstationary noise

J Ming, R Srinivasan, D Crookes - IEEE Transactions on Audio …, 2010 - ieeexplore.ieee.org
Temporal dynamics and speaker characteristics are two important features of speech that
distinguish speech from noise. In this paper, we propose a method to maximally extract …

Using posterior-based features in template matching for speech recognition

G Aradilla, J Vepa, H Bourlard - 2006 - infoscience.epfl.ch
Given the availability of large speech corpora, as well as the increasing of memory and
computational resources, the use of template matching approaches for automatic speech …

Updated MINDS report on speech recognition and understanding, Part 2 [DSP Education]

JM Baker, L Deng, S Khudanpur… - IEEE Signal …, 2009 - ieeexplore.ieee.org
This article is the second part of an updated version of the" MINDS 2006-2007 Report of the
Speech Understanding Working Group," one of five reports emanating from two workshops …

Model based design environment for data-driven embedded signal processing systems

K Sudusinghe, I Cho, M Van Der Schaar… - Procedia Computer …, 2014 - Elsevier
In this paper, we investigate new design methods for data-driven digital signal processing
(DSP) systems that are targeted to resource-and energy-constrained embedded …

Using k-Nearest Neighbor and speaker ranking for phoneme prediction

M Rizwan, DV Anderson - 2014 13th international conference …, 2014 - ieeexplore.ieee.org
Speech recognition systems are either based on parametric approach or non-parametric
approach. Parametric based systems such as HMMs have been the dominant technology for …

Improved speech-signal based frequency warping scale for cepstral feature in robust speaker verification system

SK Sarangi, G Saha - Journal of Signal Processing Systems, 2020 - Springer
Abstract Development of automatic speaker verification system (ASV) for real-world
applications remains a major challenge. In this paper, we propose an improved speech …

Noise-robust speech recognition through auditory feature detection and spike sequence decoding

PB Schafer, DZ Jin - Neural computation, 2014 - direct.mit.edu
Speech recognition in noisy conditions is a major challenge for computer systems, but the
human brain performs it routinely and accurately. Automatic speech recognition (ASR) …

Noise robust exemplar matching using sparse representations of speech

E Yılmaz, JF Gemmeke - IEEE/ACM transactions on audio …, 2014 - ieeexplore.ieee.org
Performing automatic speech recognition using exemplars (templates) holds the promise to
provide a better duration and coarticulation modeling compared to conventional approaches …

[PDF][PDF] Historical development and future directions in speech recognition and understanding

J Baker, L Deng, S Khudanpur, C Lee… - MINDS Report of the …, 2007 - www-nlpir.nist.gov
On November 13-14, 2006, a workshop entitled “Meeting of the MINDS: Future Directions for
Human Language Technology,” sponsored by the US Government's Disruptive Technology …

Noise-robust speech recognition with exemplar-based sparse representations using alpha-beta divergence

E Yılmaz, JF Gemmeke - 2014 IEEE International …, 2014 - ieeexplore.ieee.org
In this paper, we investigate the performance of a noise-robust sparse representations (SR)-
based recognizer using the Alpha-Beta (AB)-divergence to compare the noisy speech …