Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the encoder of the model on a large unlabeled multilingual dataset of 12 million (M) hours spanning over 300 languages, and fine-tuning on a smaller labeled dataset. We use multilingual pre-training with random-projection quantization and speech-text modality matching to achieve state-of-the-art performance on downstream multilingual ASR and speech-to-text translation tasks. We also demonstrate that despite using a labeled training set 1/7-th the size of that used for the Whisper model, our model exhibits comparable or better performance on both in-domain and out-of-domain speech recognition tasks across many languages.Comment: 20 pages, 7 figures, 8 table

Providing content-based services in a peer-to-peer environment

Information dissemination in wide area networks has recently garnered much attention. Two differing models, publish/subscribe and rendezvous-based multicast atop overlay networks, have emerged as the two leading approaches for this goal. Event-based publish/subscribe supports contentbased services with powerful filtering capabilities, while peer-to-peer rendezvous-based services allow for efficient communication in a dynamic network infrastructure. We describe Reach, a system that integrates these two approaches to provide efficient and scalable content-based services in a dynamic network setting.

SWAP: Shared Wireless Access Protocol (using Reciprocity)

Abstract — Wireless access points are becoming more and more prominent in the home, yet there is no incentive to encourage access point owners to share their service. We introduce SWAP, a lightweight protocol that uses reciprocity to motivate users to share service. Each node participating in SWAP stores perishable receipts that are used to calculate a user’s rating (how much the user shares his or her access point). SWAP does not use a centralized authority to store or validate receipts nor does it place an excessive burden on peers. SWAP is also robust against collusion, which we show through analysis and implementation. As demonstrated by an implementation of the most computationally expensive portions of the protocol, SWAP imposes little overhead even on mobile devices. Keywords—Community Wireless, Reciprocity, Wireless Security I

Censorship Resistance Revisited ⋆

Abstract. “Censorship resistant ” systems attempt to prevent censors from imposing a particular distribution of content across a system. In this paper, we introduce a variation of censorship resistance (CR) that is resistant to selective filtering even by a censor who is able to inspect (but not alter) the internal contents and computations of each data server, excluding only the server’s private signature key. This models a service provided by operators who do not hide their identities from censors. Even with such a strong adversarial model, our definition states that CR is only achieved if the censor must disable the entire system to filter selected content. We show that existing censorship resistant systems fail to meet this definition; that Private Information Retrieval (PIR) is necessary, though not sufficient, to achieve our definition of CR; and that CR is achieved through a modification of PIR for which known implementations exist.