منابع مشابه
Performance of Discriminatively Tra Aurora2 and Aur
The design of acoustic models involves two main tasks: feature extraction and data modeling; and hidden Markov modeling (HMM) is commonly used in contemporary automatic speech recognition. In the past, discriminative training has been applied successfully to refine HMM parameters that are initially trained by EM algorithm. Recently, we applied discriminative training in the feature extraction p...
متن کاملIntegration of noise reduction algorithms for Aurora2 task
To achieve high recognition performance for a wide variety of noise and for a wide range of signal-to-noise ratios, this paper presents the integration of four noise reduction algorithms: spectral subtraction with smoothing of time direction, temporal domain SVD-based speech enhancement, GMM-based speech estimation and KLT-based comb-filtering. Recognition results on the Aurora2 task show that ...
متن کاملPerformance of discriminatively trained auditory features on Aurora2 and Aurora3
ABSTRACT The design of acoustic models involves two main tasks: feature extraction and data modeling; and hidden Markov modeling (HMM) is commonly used in contemporary automatic speech recognition. In the past, discriminative training has been applied successfully to refine HMM parameters that are initially trained by EM algorithm. Recently, we applied discriminative training in the feature ext...
متن کاملEvaluation of the SPLICE algorithm on the Aurora2 database
This paper describes recent improvements to SPLICE, Stereo-based Piecewise Linear Compensation for Environments, which produces an estimate of cepstrum of undistorted speech given the observed cepstrum of distorted speech. For distributed speech recognition applications, SPLICE can be placed at the server, thus limiting the processing that would take place at the client. We evaluated this algor...
متن کاملData-driven Temporal Fil Different Optimization Cri Aurora2 Dat
In deriving the data-driven temporal filters for speech features, the Linear Discriminant Analysis (LDA) has been shown to be successful in improving the feature robustness [1,2,3]. In our previous works [4,5] it was shown that the criteria of Principal Component Analysis (PCA) and Minimum Classification Error (MCE) can also be used to obtain the data-driven temporal filters in improving the sp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 1922
ISSN: 0027-0644,1520-0493
DOI: 10.1175/1520-0493(1922)50<257c:hoa>2.0.co;2