Robust Cochlear-Model-Based Speech Recognition
نویسندگان
چکیده
منابع مشابه
An environment model-based robust speech recognition
In this paper, a new approach named environmental discrimination learning (EDL) is proposed to remove the effects of the environment noises including the additive noise and the channel distortions. This method optimizes the environment parameters by the minimum classification error (MCE) criterion which trains the parameters of a given class dependently on the whole classes. The EDL approach ut...
متن کاملRobust Speech Recognition using Model
Maintaining a high level of robustness for Automatic Speech Recognition (ASR) systems is especially challenging when the background noise has a time-varying nature. We have implemented a Model-Based Feature Enhancement (MBFE) technique that not only can easily be embedded in the feature extraction module of a recogniser, but also is intrinsically suited for the removal of non-stationary additiv...
متن کاملImproving the performance of MFCC for Persian robust speech recognition
The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...
متن کاملA reference model weighting-based method for robust speech recognition
In this paper a reference model weighting (RMW) method is proposed for fast hidden Markov model (HMM) adaptation which aims to use only one input test utterance to online estimate the characteristic of the unknown test noisy environment. The idea of RMW is to first collect a set of reference HMMs in the training phase to represent the space of noisy environments, and then synthesize a suitable ...
متن کاملNanyang Technological University Model - Based Noise Robust Speech Recognition
Noise robustness is a challenging problem when automatic speech recognition (ASR) system is deployed in real life applications. This report examines techniques to improve the robustness of ASR systems. Particularly, we focus on a group of model-based noise robust techniques, called vector Taylor series (VTS) method, that adapt the acoustic model of ASR systems towards noisy test data using the ...
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: Computers
سال: 2019
ISSN: 2073-431X
DOI: 10.3390/computers8010005