RawNet: Fast End-to-End Neural Vocoder

Neural networks based vocoders have recently demonstrated the powerful ability to synthesize high quality speech. These models usually generate samples by conditioning on some spectrum features, such as Mel-spectrum. However, these features are extracted by using speech analysis module including some processing based on the human knowledge. In this work, we proposed RawNet, a truly end-to-end neural vocoder, which use a coder network to learn the higher representation of signal, and an autoregressive voder network to generate speech sample by sample. The coder and voder together act like an auto-encoder network, and could be jointly trained directly on raw waveform without any human-designed features. The experiments on the Copy-Synthesis tasks show that RawNet can achieve the comparative synthesized speech quality with LPCNet, with a smaller model architecture and faster speech generation at the inference step.Comment: Submitted to Interspeech 2019, Graz, Austri

Attention-Based End-to-End Speech Recognition on Voice Search

Recently, there has been a growing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. In this paper, we explore the use of attention-based encoder-decoder model for Mandarin speech recognition on a voice search task. Previous attempts have shown that applying attention-based encoder-decoder to Mandarin speech recognition was quite difficult due to the logographic orthography of Mandarin, the large vocabulary and the conditional dependency of the attention model. In this paper, we use character embedding to deal with the large vocabulary. Several tricks are used for effective model training, including L2 regularization, Gaussian weight noise and frame skipping. We compare two attention mechanisms and use attention smoothing to cover long context in the attention model. Taken together, these tricks allow us to finally achieve a character error rate (CER) of 3.58% and a sentence error rate (SER) of 7.43% on the MiTV voice search dataset. While together with a trigram language model, CER and SER reach 2.81% and 5.77%, respectively

Study on De-gendering Rape Crime

At present, our criminal legislation stipulates that the object of rape crime is only adult female and female, the subject of crime in addition to joint crime and indirect crime can be female the rest of the male, this recognition is gradually behind the social practice. In addition to men and women, intersex people and transgender people are increasingly appearing in the public eye, and their rights should also be protected. Serious assaults on men and other gender people, such as rape, are not suitable for the crime of forcible indecency. Rape only protect women’s sexual autonomy to no longer meet the needs of reality, also lags behind other typical countries or regions of the act, the gender differences cannot be does not constitute a rape, the premise of any gender can be the object of crime and the crime of rape, which is reflect equality, guarantee of human rights

Overheated Topological Hall Effect: How Possible Artifacts Emerge?

Topological Hall effect (THE) originates from the real-space Berry phase that an electron gains when its spin follows the spatially varying non-trivial magnetization textures, such as skyrmions. Such topologically protected magnetization textures can provide great potential for information storage and processing, which spurs a new wave of THE research. Since directly imaging the skyrmions or detecting the magnetic diffraction of skyrmion lattice are more challenging than conducting Hall measurements, THE has been widely used to attest the presence of skyrmions. However, as the key feature of THE, the bump/dip in Hall signal is not a sufficient proof of THE [Phys. Rev. B, \textbf{98},180408(2018) and Phys. Rev. B. \textbf{98}, 214440(2018)]. Here, we use empirical numerical modeling to demonstrate all possible THE-like signals that two anomalous Hall effect (AHE) signals with opposite signs can superpose. We accentuate that similar Hall signals observed in experiments require scrupulous re-examination to claim the advent of THE and related skyrmions. In addition, the origin of two-channel AHE in several representative examples are also been analyzed

Gas pressure sintering of BN/Si3N4 wave-transparent material with Y2O3–MgO nanopowders addition

AbstractBN/Si3N4 ceramics performed as wave-transparent material in spacecraft were fabricated with boron nitride powders, silicon nitride powders and Y2O3–MgO nanopowders by gas pressure sintering at 1700°C under 6MPa in N2 atmosphere. The effects of Y2O3–MgO nanopowders on densification, phase evolution, microstructure and mechanical properties of BN/Si3N4 material were investigated. The addition of Y2O3–MgO nanopowders was found beneficial to the mechanical properties of BN/Si3N4 composites. The BN/Si3N4 ceramics with 8wt% Y2O3–MgO nanopowders showed a relative density of 80.2%, combining a fracture toughness of 4.6MPam1/2 with an acceptable flexural strength of 396.5MPa