Abstract What is “big”? Time & Space? Expense? Pounds? Power? Size of machine? Size of market? We will discuss many of these dimensions, but focus on throughput and latency (mobility of data). If our clouds[…]
View Seminar Video Abstract Modern approaches to machine translation, like those used in Google’s online translation system, are data-driven. Statistical translation models are trained using bilingual parallel texts, which consist of sentences in one language[…]
Abstract The speech team at Google has built speech recognition systems in more that 40 languages in little more than 3 years. In this talk I will describe the history of this project and what[…]
Abstract Despite all the recent successes of machine translation, when it comes to high quality publishable translation, human translators are still unchallenged. Since we can’t beat them, can we help them to become more productive?[…]
View Seminar Video Abstract The i–vector extraction process is characterized by an intrinsic uncertainty represented by the i–vector posterior covariance. The usual PLDA models, however, ignore such uncertainty and perform speaker inference based only on[…]
View Seminar Video Abstract I will describe the speaker identification (SID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance[…]
Abstract During early language acquisition, infants must learn both a lexicon and a model of phonetics that explains how lexical items can vary in pronunciation– for instance “you” might be realized as ‘you’ with a[…]
