نتایج جستجو برای: noisy speech

تعداد نتایج: 146656  

2001
Xiaoqing Yu Wanggen Wan Daniel Pak-Kong Lun

The main purpose of this paper is to present how to raise the speech recognition performance in noisy environment. So far the most popularly used speech feature in speech recognition is probably the so-called MFCC. The recognition rate of speech recognition algorithm using MFCC and CDHMM is known to be very high in clean speech environment, but it deteriorates greatly in noisy environment, espe...

2002
Yariv Ephraim

We investigate the performance of a recent algorithm €or linear predictive (LP) modeling of speech signals, which have been degraded by uncorrelated additive noise, as a front-end processor in a speech recognition system. The system is speaker dependent, and recognizes isolated words, based on dynamic time warping principles. The LP model for the clean speech is estimated through appropriate co...

2006
Xiao Xiong

The objective of this research is to develop feature compensation techniques to make automatic speech recognition (ASR) systems more robust to noise distortions. The research is important as the performance of ASR systems degrades dramatically in adverse environments, and hence greatly limits the speech recognition application deployment. In this report, we aim to build a generic framework for ...

Speech recognition has achieved great improvements recently. However, robustness is still one of the big problems, e.g. performance of recognition fluctuates sharply depending on the speaker, especially when the speaker has strong accent and difference Accents dramatically decrease the accuracy of an ASR system. In this paper we apply three new methods of feature extraction including Spectral C...

2000
A. S. Madhukumar A. B. Premkumar

This paper proposes an architecture for low bit rate coding of noisy speech. The input noisy speech is decomposed into multiresolution signal components using wavelet transform. An iterative Wiener filtering is used at each level of wavelet analysis to enhance speech. The system model that evolves during enhancement is processed further to get optimal parameters for the quantization. A multista...

2010
Frank Rudzicz

Modern automatic speech recognition is ineffective at understanding relatively unintelligible speech caused by neuro-motor disabilities collectively called dysarthria. Since dysarthria is primarily an articulatory phenomenon, we are collecting a database of vocal tract measurements during speech of individuals with cerebral palsy. In this paper, we demonstrate that articulatory knowledge can re...

2003
Guokang Fu Ta-Hsin Li

Accurate recognition of speech in noisy environment is still an obstacle for wider application of speech recognition technology. Noise reduction, which is aimed at cleaning the corrupted testing signal to match the ideal training conditions, remain to be an effective approach to improving the accuracy of speech recognition in noisy environment. This paper introduces a new algorithm of noise red...

2012
Philip Harding Ben P. Milner

A method of speech enhancement is developed that reconstructs clean speech from a set of acoustic features using a sinusoidal model of speech. This is a significant departure from traditional filtering-based methods of speech enhancement. A major challenge with this approach is to estimate accurately the acoustic features (voicing, fundamental frequency, spectral envelope) from noisy speech. Th...

Journal: :CoRR 2018
Nikolay Matveev Kirill Andreev Alexey Frolov Andrey M. Turlikov

We address the problem of massive random access for an uncoordinated Gaussian multiple access channel (MAC). The performance of T-fold irregular repetition slotted ALOHA (IRSA) scheme for this channel is investigated. The main difference of this scheme in comparison to IRSA is as follows: any collisions of order up to T can be resolved with some probability of error introduced by Gaussian noise...

2005
Hema Raghavan James Allan

Many proper names are spelled inconsistently in speech recognizer output, posing a problem for applications where locating mentions of named entities is critical. We model the distortion in the spelling of a name due to the speech recognizer as the effect of a noisy channel. The models follow the framework of the IBM translation models. The model is trained using a parallel text of closed capti...

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