Mutual Learning of Single- and Multi-Channel End-to-End Neural Diarization

Due to the high performance of multi-channel speech processing, we can use the outputs from a multi-channel model as teacher labels when training a single-channel model with knowledge distillation. To the contrary, it is also known that single-channel speech data can benefit multi-channel models by mixing it with multi-channel speech data during training or by using it for model pretraining. This paper focuses on speaker diarization and proposes to conduct the above bi-directional knowledge transfer alternately. We first introduce an end-to-end neural diarization model that can handle both single- and multi-channel inputs. Using this model, we alternately conduct i) knowledge distillation from a multi-channel model to a single-channel model and ii) finetuning from the distilled single-channel model to a multi-channel model. Experimental results on two-speaker data show that the proposed method mutually improved single- and multi-channel speaker diarization performances.Comment: Accepted to IEEE SLT 202

Reduction of parasitic reaction in high-temperature AlN growth by jet stream gas flow metal–organic vapor phase epitaxy

AlGaN-based deep ultraviolet light-emitting diodes (LEDs) have a wide range of applications such as medical diagnostics, gas sensing, and water sterilization. Metal–organic vapor phase epitaxy (MOVPE) method is used for the growth of all-in-one structures, including doped layer and thin multilayers, using metal–organic and gas source raw materials for semiconductor devices. For AlN growth with high crystalline quality, high temperature is necessary to promote the surface migration of Al atoms and Al-free radicals. However, increase in temperature generates parasitic gas-phase prereactions such as adduct formation. In this work, AlN growth at 1500 °C by a stable vapor phase reaction has been achieved by jet stream gas flow metal–organic vapor phase epitaxy. The AlN growth rate increases with gas flow velocity and saturates at ~ 10 m/s at room temperature. Moreover, it is constant at an ammonia flow rate at a V/III ratio from 50 to 220. These results demonstrate the reduction in adduct formation, which is a typical issue with the vapor phase reaction between triethylaluminum and ammonia. The developed method provides the in-plane uniformity of AlN thickness within 5%, a low concentration of unintentionally doped impurities, smooth surface, and decrease in dislocation density because of the suppression of parasitic reactions