- Publications
- Influence
Claim Your Author Page
Ensure your research is discoverable on Semantic Scholar. Claiming your author page allows you to personalize the information displayed and manage publications (all current information on this profile has been aggregated automatically from publisher and metadata sources).
Abstract A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segmentation is… Continue Reading
Semantic slot filling is one of the most challenging problems in spoken language understanding (SLU). In this paper, we propose to use recurrent neural networks (RNNs) for this task, and present… Continue Reading
Sequence-to-sequence deep learning has recently emerged as a new paradigm in supervised learning for spoken language understanding. However, most of the previous studies explored this framework for… Continue Reading
We present statistical models for morphological disambiguation in agglutinative languages, with a specific application to Turkish. Turkish presents an interesting problem for statistical models as… Continue Reading
The ICSI multi-document summarization system relies on a general framework that casts summarization as a global optimization problem with an integer linear programming solution. Our primary… Continue Reading
We describe improvements to our 2008 system that result in a top-performing summarization system. The motivating ideas are (1) improve sentence boundary detection to avoid damaging errors in… Continue Reading
This paper presents the results of a study on information extraction from unrestricted Turkish text using statistical language processing methods. In languages like English, there is a very small… Continue Reading
We present our recent and ongoing work on applying deep learning techniques to spoken language understanding (SLU) problems. The previously developed deep convex network (DCN) is extended to its… Continue Reading
Scoring sentences in documents given abstract summaries created by humans is important in extractive multi-document summarization. In this paper, we formulate extractive summarization as a two step… Continue Reading