کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
407988 678242 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nonlinear enhancement of noisy speech, using continuous attractor dynamics formed in recurrent neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Nonlinear enhancement of noisy speech, using continuous attractor dynamics formed in recurrent neural networks
چکیده انگلیسی

Here, formation of continuous attractor dynamics in a nonlinear recurrent neural network is used to achieve a nonlinear speech denoising method, in order to implement robust phoneme recognition and information retrieval. Formation of attractor dynamics in recurrent neural network is first carried out by training the clean speech subspace as the continuous attractor. Then, it is used to recognize noisy speech with both stationary and nonstationary noise. In this work, the efficiency of a nonlinear feedforward network is compared to the same one with a recurrent connection in its hidden layer. The structure and training of this recurrent connection, is designed in such a way that the network learns to denoise the signal step by step, using properties of attractors it has formed, along with phone recognition. Using these connections, the recognition accuracy is improved 21% for the stationary signal and 14% for the nonstationary one with 0db SNR, in respect to a reference model which is a feedforward neural network.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 2716–2724
نویسندگان
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