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Writer-based and reader-based views of text-meaning are reflected by the respective questions “What is the author trying to tell me?” and “What does this text mean to me personally?” Contemporary computational linguistics, however, generally takes neither view. But this is not adequate for the development of sophisticated applications such as intelligence gathering and question answering. I discuss...
The link between words and the world is made easier if we have conceptualized the world in a way that language indicates. In the effort I will describe, we have constructed a number of core formal theories, trying to capture the abstract structure that underlies language and enable literal and metaphorical readings to be seen as specializations of the abstract structures. In the core theories, we...
The n-gram model is standard for large vocabulary speech recognizers. Many attempts were made to improve on it. Language models were proposed based on grammatical analysis, artificial neural networks, random forests, etc. While the latter give somewhat better recognition results than the n-gram model, they are not practical, particularly when large training data bases (e.g., from world wide web) are...
Prosody is clearly valuable for human understanding, but can be difficult to model in spoken language technology. This talk describes a “direct modeling” approach, which does not require any hand-labeling of prosodic events. Instead, prosodic features are extracted directly from the speech signal, based on time alignments from automatic speech recognition. Machine learning techniques then determine...
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