This paper describes an unconventional way to use wav2vec 2.0 representations for voice conversion (VC) purpose. Our experiment shows that aggregate of hidden representations from wav2vec 2.0 layers is more effective in VC than using last-layer representation only. In particular, the aggregate of all hidden representations is dependent on a mainly required characteristic (e.g. vocal or linguistic) by a speech task—but such results are consistent on different datasets for the same task. Based on these results, we propose Wav2vec-VC that uses wav2vec 2.0 hidden-layer representations as input to the disentanglement-based VC. Given a target (/source) utterance, Wav2vec-VC gets an aggregated hidden representation weighted in order to perform the speaker (/content)-related tasks, and feeds it to a speaker (/content) encoder whose output is combined at a decoder to synthesize a voice-converted utterance. Our evaluation shows that Wav2vec-VC outperforms SOTA VC models in terms of both voice similarity and speech intelligibility.

The use of smartphones as voice recorders has made it easy to record audios as proof of conversations, but sharing of such audio evidence incurs speech and voice privacy risks. However, protecting speech/voice privacy without losing audio authenticity is challenging. The conventional post-process redaction and voice conversion of audio recordings, which invalidate their original signatures, make the audio unverifiable and prone to tampering. In this paper, we present Overo, an audio recording/sharing solution that supports privacy processing without losing audio authenticity. Overo records a realtime audio stream in the standard AAC-encoded format and allows privacy post-processing prior to sharing of audios while keeping their original signatures valid (even after the post redaction and voice conversion), guaranteeing no tampering since the time of their recording. Therefore, users can post-process their recordings to desired levels of privacy on speech (what content to redact) and speakers (whose voice to disguise) at the time of audio release, and still prove their authenticity. Overo is readily implementable in today's commodity smartphones. Our prototype on iPhones/Android phones demonstrates the production of AAC-compliant, tamperproof, and self-authenticating audios with speech/voice privacy protected based on users' post-recording decisions.

With various IoT cameras today, sharing of their video evidences, while benefiting the public, threatens the privacy of individuals in the footage. However, protecting visual privacy without losing video authenticity is challenging. The conventional post-process blurring would open the door for posterior fabrication, whereas the realtime blurring results in poor quality, low-frame-rate videos due to the limited processing power of commodity cameras. This paper presents Pinto, a software-based solution for producing privacy-protected, forgery-proof, and high-frame-rate videos using low-end IoT cameras. Pinto records a realtime video stream at a fast rate and allows post-processing for privacy protection prior to sharing of videos while keeping their original, realtime signatures valid even after the post blurring, guaranteeing no content forgery since the time of their recording. Pinto is readily implementable in today's commodity cameras. Our prototype on three different embedded devices, each deployed in a specific application context---on-site, vehicular, and aerial surveillance---demonstrates the production of privacy-protected, forgery-proof videos with frame rates of 17--24 fps, comparable to those of HD videos.

The feasibility conditions of interference alignment (IA) are analyzed for interfering broadcast-multiple-access channels in which one cell operates as downlink but the other cell operates as uplink. Under a general multiple-input and multiple-output antenna configuration, a necessary condition and a sufficient condition for one-shot linear IA are established, i.e., linear IA without symbol or time extension. In various example networks of interest, the optimal sum degrees of freedom (DoFs) are characterized by the derived necessary condition and sufficient condition. For symmetric DoF within each cell, a sufficient condition is established in a more compact expression, which yields the necessary and sufficient condition for a class of symmetric DoFs. An iterative construction of transmit and receive beamforming vectors is further proposed, which provides a specific beamforming design satisfying one-shot IA. Simulation results demonstrate that the proposed IA not only achieves larger DoF, but also significantly improves the sum rate over the single-cell operation in the practical signal-to-noise ratio regime.

Due to the tremendous growth of mobile data traffic, some technologies from small cell deployment are still ongoing as nominated solutions. Without enlarged wired backhaul capacity, however, the performance of small cell techniques are inevitably degraded. The approach employing the storage capacity in order to off-load the backhaul capacity, as known as femto-caching, has been proposed to minimize the delay within downloading data [1]. In this paper, we consider more practical scenario such as distribution of users' position in whole networks and extend the previous researches in the manner of file placement strategies. Simulation results verify that our proposed scheme has better performance gains with respect to increased opportunity to obtain more various downloading data if helpers' coverages are overlapped.

In this paper we derive the power loading method for Band Aggregation (BA) Single Carrier-Frequency Division Multiple Access (SC-FDMA) with Zero-Forcing Frequency Domain Equalizer (ZF-FDE). In previous research [6], they derive the optimal power allocation for SC-FDMA with single band, however, this result cannot directly be extended to multiple bands. Thus, we proposed sub-optimal the two stages power loading scheme for SC-FDMA with ZF-FDE in multiple bands. First, we optimize the total powers of each band and then powers of each sub-carrier are optimized by using optimal power in the first step. Simulation results show that the proposed power control is particularly effective in improving the achievable data rate at low Signal to Noise Ratio (SNR).