Produção Nacional
Deep Neural Networks for Acoustic Modeling in the Presence of Noise
2018; Institute of Electrical and Electronics Engineers; Volume: 16; Issue: 3 Linguagem: Inglês
10.1109/tla.2018.8358674
ISSN1548-0992
AutoresLuciana Maiara Queiroz de Santana, Rafael M. Santos, Leonardo Nogueira Matos, Hendrik Macedo,
Tópico(s)Speech and Audio Processing
ResumoSystems using deep neural network (DNN) have shown promising results in automatic speech recognition (ASR), where one of the biggest challenges is the recognition in noisy speech signals. We have combined two famous architectures of deep learning, the convolutional neural networks (CNN) for acoustic approach and a recurrent architecture with connectionist temporal classification (CTC) for sequential modeling, in order to decode the frames in a sequence forming a word. Experimental results show that the proposed architecture achieves improved performance over classical models, such as hidden model Markov (HMM) for labeling in variable time sequences in BioChaves database.
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