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In this paper, we report research results on modeling the parameters of an improved time-frequency trajectory excitation (ITFTE) and spectral envelopes of an LPC vocoder with a long short-term memory (LSTM)-based recurrent neural network (RNN) for high-quality text-to-speech (TTS) systems. The ITFTE vocoder has been shown to significantly improve the perceptual quality of statistical parameter-based...
We propose a new timing error correction scheme for area-efficient design of flip-flop based pipeline. Key features in the proposed scheme are 1) one-cycle error correction using a new local stalling scheme and 2) selective replacement of the error detection and correction flip-flops in critical paths only. A 32-bit MIPS testchip in a 65 nm CMOS technology has been implemented as a testbed. By employing...
This paper proposes a multi-class learning (MCL) algorithm for a deep neural network (DNN)-based statistical parametric speech synthesis (SPSS) system. Although the DNN-based SPSS system improves the modeling accuracy of statistical parameters, its synthesized speech is often muffled because the training process only considers the global characteristics of the entire set of training data, but does...
This paper proposes a constrained two-layer compression technique for electrocardiogram (ECG) waves, of which encoded parameters can be directly used for the diagnosis of arrhythmia. In the first layer, a single ECG beat is represented by one of the registered templates in the codebook. Since the required coding parameter in this layer is only the codebook index of the selected template, its compression...
This paper proposes an improved time-frequency trajectory excitation (TFTE) modeling method for a statistical parametric speech synthesis system. The proposed approach overcomes the dimensional variation problem of the training process caused by the inherent nature of the pitch-dependent analysis paradigm. By reducing the redundancies of the parameters using predicted average block coefficients (PABC),...
This paper proposes a speech enhancement algorithm for pathological voices using a time-frequency trajectory excitation (TFTE) modeling. The TFTE model has a capability of delicately controlling the periodic and non-periodic excitation components by taking a single pitch based decomposition process. By investigating the difference of frequency characteristics between pathological and normal voices,...
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