In digital video transmission, latency is caused not only by network delays but also by overhead in various devices. This study proposes the design of a low-latency IP video transmission (less than 40 ms) that can augment human vision via IP networks. In addition, we also provide a remote control experience to demonstrate that low-latency visual transmission facilitates remote collaboration between humans and robots. In a demo with the low-latency system, users will be able to experience remote control operations like never before, gaining a sense of agency that goes beyond a mere remote experience.

To resolve disputes between servicers providing web services and their users, non-repudiable evidence is crucial because it allows one party to dismiss the denial of facts or false allegations. We propose a logger that securely records web requests and responses in a Trusted Execution Environment (TEE) to generate non-repudiable evidence for web services, which we call LogNEWT: Logger for Non-rEpudiation of Web with TEE. LogNEWT solves security issues in deploying LibSEAL to practical web services, i.e., logger-bypassing, undefined user management, and complex logger verification. In addition, LogNEWT can be transparently deployed to the existing web services.

In this paper, we propose an algorithm to improve the naturalness of the reconstructed glossectomy patient's speech that is generated by voice conversion to enhance the intelligibility of speech uttered by patients with a wide glossectomy. While existing VC algorithms make it possible to improve intelligibility and naturalness, the result is still not satisfying. To solve the continuing problems, we propose to directly modify the speech waveforms using a spectrum differential. The motivation is that glossectomy patients mainly have problems in their vocal tract, not in their vocal cords. The proposed algorithm requires no source parameter extractions for speech synthesis, so there are no errors in source parameter extractions and we are able to make the best use of the original source characteristics. In terms of spectrum conversion, we evaluate with both GMM and DNN. Subjective evaluations show that our algorithm can synthesize more natural speech than the vocoder-based method. Judging from observations of the spectrogram, power in high-frequency bands of fricatives and stops is reconstructed to be similar to that of natural speech.