2,883 research outputs found
Exploiting the semantic web for unsupervised spoken language understanding.
ABSTRACT This paper proposes an unsupervised training approach for SLU systems that leverages the structured semantic knowledge graphs of the emerging Semantic Web. The approach creates natural language surface forms of entity-relation-entity portions of knowledge graphs using a combination of web search retrieval and syntax-based dependency parsing. The new forms are used to train an SLU system in an unsupervised manner. This paper tests the approach on the problem of intent detection, and shows that the unsupervised training procedure matches the performance of supervised training over operating points important for commercial applications. Index Terms-spoken language understanding, intent detection, structured knowledge-based search, semantic we
Towards a Knowledge Graph based Speech Interface
Applications which use human speech as an input require a speech interface
with high recognition accuracy. The words or phrases in the recognised text are
annotated with a machine-understandable meaning and linked to knowledge graphs
for further processing by the target application. These semantic annotations of
recognised words can be represented as a subject-predicate-object triples which
collectively form a graph often referred to as a knowledge graph. This type of
knowledge representation facilitates to use speech interfaces with any spoken
input application, since the information is represented in logical, semantic
form, retrieving and storing can be followed using any web standard query
languages. In this work, we develop a methodology for linking speech input to
knowledge graphs and study the impact of recognition errors in the overall
process. We show that for a corpus with lower WER, the annotation and linking
of entities to the DBpedia knowledge graph is considerable. DBpedia Spotlight,
a tool to interlink text documents with the linked open data is used to link
the speech recognition output to the DBpedia knowledge graph. Such a
knowledge-based speech recognition interface is useful for applications such as
question answering or spoken dialog systems.Comment: Under Review in International Workshop on Grounding Language
Understanding, Satellite of Interspeech 201
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