ATIS

This paper describes the initial development of a natural language text processor, as the first step in an INRS dialogue-by-voice system. The eventual system will accept natural, spontaneous speech from …...

We describe the results that SRI International achieved on the February 1992 ATIS Speech and Natural Language Sys- tem Test. The basic architecture of the system is described, including a …...

Prosodic patterns provide important cues for resolving syn- tactic ambiguity, and might he used to improve the accu- racy of automatic speech understanding. With this goal, we propose a method …...

This paper presents the Semantic Linker, the fallbaek component used by the the DELPHI natural language component of the BBN spoken language system HARC. The Semantic Linker is invoked when …...

The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuous speech recogni- tion, we can use the same …...

This paper describes PEGASUS, a spoken language inter- face for on-line air travel planning that we have recently devel- oped. PEGASUS leverages off our spoken language technology development in the …...

Several recent efforts in statistical nat- ural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; Levin and Pierac- cini, …...

We develop a people-centered computational history of science that tracks authors over top- ics and apply it to the history of computa- tional linguistics. We present four findings in this …...

We present the first unsupervised ap- proach for semantic parsing that rivals the accuracy of supervised approaches in translating natural-language questions to database queries. Our GUSP system produces a semantic …...

Semantic parsing has made significant progress, but most current semantic parsers are extremely slow (CKY-based) and rather primitive in representation. We introduce three new techniques to tackle these problems. First, …...

AbstractWe present methods for multi-task learning that take advantage of natural groupings of related tasks. Task groups may be defined along known properties of the tasks, such as task domain …...

AbstractSelf-attention networks (SAN) have shown promising performance in various Natural Language Processing (NLP) scenarios, especially in machine translation. One of the main points of SANs is the strength of capturing …...

AbstractRecently, spoken language understanding (SLU) has attracted extensive research interests, and various SLU datasets have been proposed to promote the development. However, most of the existing methods focus on a …...

Neural-based models have achieved outstand- ing performance on slot filling and intent clas- sification, when fairly large in-domain train- ing data are available. However, as new do- mains are frequently …...

There is a recent interest in investigating few- shot NER, where the low-resource target do- main has different label sets compared with a resource-rich source domain. Existing meth- ods use …...

Abstract“Semantic parsing aims to convert natural language utterances to logical forms. A critical challenge for constructing semantic parsers is the lack of labeled data. In this paper, we propose a …...

AbstractIn text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction. However, …...

AbstractSemantic parsing considers the task of mapping a natural language sentence into a target formal representation, where various sophisticated sequence-to-sequence (seq2seq) models have been applied with promising results. Generally, these …...