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pro vyhledávání: '"BÜTHE, JAN"'
Neural vocoders are now being used in a wide range of speech processing applications. In many of those applications, the vocoder can be the most complex component, so finding lower complexity algorithms can lead to significant practical benefits. In
Externí odkaz:
http://arxiv.org/abs/2405.21069
Speech codec enhancement methods are designed to remove distortions added by speech codecs. While classical methods are very low in complexity and add zero delay, their effectiveness is rather limited. Compared to that, DNN-based methods deliver high
Externí odkaz:
http://arxiv.org/abs/2309.14521
Pitch estimation is an essential step of many speech processing algorithms, including speech coding, synthesis, and enhancement. Recently, pitch estimators based on deep neural networks (DNNs) have have been outperforming well-established DSP-based t
Externí odkaz:
http://arxiv.org/abs/2309.14507
Classical speech coding uses low-complexity postfilters with zero lookahead to enhance the quality of coded speech, but their effectiveness is limited by their simplicity. Deep Neural Networks (DNNs) can be much more effective, but require high compl
Externí odkaz:
http://arxiv.org/abs/2307.06610
GAN vocoders are currently one of the state-of-the-art methods for building high-quality neural waveform generative models. However, most of their architectures require dozens of billion floating-point operations per second (GFLOPS) to generate speec
Externí odkaz:
http://arxiv.org/abs/2212.04532
Despite recent advancements in packet loss concealment (PLC) using deep learning techniques, packet loss remains a significant challenge in real-time speech communication. Redundancy has been used in the past to recover the missing information during
Externí odkaz:
http://arxiv.org/abs/2212.04453
Recently, GAN vocoders have seen rapid progress in speech synthesis, starting to outperform autoregressive models in perceptual quality with much higher generation speed. However, autoregressive vocoders are still the common choice for neural generat
Externí odkaz:
http://arxiv.org/abs/2108.04051
Autor:
Büthe, Jan
In this paper we present an analytic altorithm which calculates almost sharp bounds for the normalized error term $(t-\psi(t))/\sqrt{t}$ for $t\leq x$ in expected run time $O(x^{1/2+\varepsilon})$ for every $\varepsilon>0$. The method has been implem
Externí odkaz:
http://arxiv.org/abs/1511.02032
Autor:
Büthe, Jan
Publikováno v:
Acta Arith. 171 (2015), 183-195
The function $\sum_{p\leq x} \frac{1}{p} - \log\log(x) - M$ is known to change sign infinitely often, but so far all calculated values are positive. In this paper we prove that the first sign change occurs well before $\exp(495.702833165)$.
Comm
Comm
Externí odkaz:
http://arxiv.org/abs/1503.01277
Autor:
Büthe, Jan
Publikováno v:
Acta Arith. 166 (2014), 289-299
We prove explicit upper bounds for weighted sums over prime numbers in arithmetic progressions with slowly varying weight functions. The results generalize the well-known Brun-Titchmarsh inequality.
Comment: 11 pages, to appear in Acta Arithmeti
Comment: 11 pages, to appear in Acta Arithmeti
Externí odkaz:
http://arxiv.org/abs/1410.7561