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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances

Weigelt, Sebastian; Steurer, Vanessa; Hey, Tobias; Tichy, Walter F.

Abstract (englisch):
Systems with conversational interfaces are rather popular nowadays. However, their full potential is not yet exploited. For the time being, users are restricted to calling predefined functions. Soon, users will expect to customize systems to their needs and create own functions using nothing but spoken instructions. Thus, future systems must understand how laypersons teach new functionality to intelligent systems. The understanding of natural language teaching sequences is a first step toward comprehensive end-user programming in natural language. We propose to analyze the semantics of spoken teaching sequences with a hierarchical classification approach. First, we classify whether an utterance constitutes an effort to teach a new function or not. Afterward, a second classifier locates the distinct semantic parts of teaching efforts: declaration of a new function, specification of intermediate steps, and superfluous information. For both tasks we implement a broad range of machine learning techniques: classical approaches, such as Naïve Bayes, and neural network configurations of various types and architectures, such as bidirectional LSTMs. ... mehr

DOI: 10.1142/S1793351X20400097
Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 06.2020
Sprache Englisch
Identifikator ISSN: 1793-351X, 1793-7108
KITopen-ID: 1000124405
Erschienen in International journal of semantic computing
Band 14
Heft 2
Seiten 249–272
Schlagwörter Programming in natural language, natural language understanding, end-user programming, conversational interfaces, spoken language understanding, natural language processing, computational linguistics, naturalistic programming, machine learning, neural networks, intelligent systems, artificial intelligence
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