—Due to the rapid growth of real-time applications and the ubiquity of IEEE 802.11 MAC as a layer-2 protocol for wireless local area networks (WLANs), it is of increasing interes...
Yan Gao, Chee Wei Tan, Ying Huang, Zheng Zeng, P. ...
This paper introduces a new neural network language model (NNLM) based on word clustering to structure the output vocabulary: Structured Output Layer NNLM. This model is able to h...
Hai Son Le, Ilya Oparin, Alexandre Allauzen, Jean-...
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...
In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of i...
Sangnam Nam, Michael E. Davies, Michael Elad, R&ea...
Previous analysis of content fingerprints has mainly focused on the case of independent and identically distributed fingerprints. Practical fingerprints, however, exhibit corre...
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Repetition is a core principle in music. This is especially true for popular songs, generally marked by a noticeable repeating musical structure, over which the singer performs va...
Distributed representations of words are attractive since they provide a means for measuring word similarity. However, most approaches to learning distributed representations are ...
This paper combines a parameter generation algorithm and a model optimization approach with the model-integration-based voice conversion (MIVC). We have proposed probabilistic int...
In this paper, we call the pattern classification problem that consists in assigning a category label to a long audio signal based on its semantic content as Generic Audio Documen...