View Seminar Video Abstract We present two algorithms for sparse learning, where our goal is to estimate a target function that is a sparse linear combination of a set of basis functions. The first method[…]
View Seminar Video Abstract Web search engines sift through billions of documents to identify those most likely to be relevant to a short natural language query. This functionality can be exploited to relate queries not[…]
View Seminar Video Abstract The development of an automatic speech recognizer is typically a highly supervised process involving the specification of phonetic inventories, lexicons, acoustic and language models, along with annotated training corpora. Although some[…]
View Seminar Video Abstract Traditional natural language processing systems have focused on modeling the deep, human-like level of text understanding, by integrating syntax and semantics. However, they overlooked a key requirement for scalability: learning. Modern[…]
View Seminar Video Abstract The ability to automatically predict appropriate prominence patterns is considered a key factor for improving the naturalness of text-to-speech synthesis systems. I will present results from a large human preference experiment[…]
View Seminar Video Abstract The interest in system combination for machine translation has recently increased due to programs involving multiple sites. In programs, such as the DARPA GALE, the sites develop MT systems independently for[…]
View Seminar Video Abstract Early word-spotting systems processed the audio signal to produce phonetic transcripts without the use of an automatic speech recognition (ASR) system. In the past decade, most of the research efforts on[…]
