21,950 research outputs found
A Personalized System for Conversational Recommendations
Searching for and making decisions about information is becoming increasingly
difficult as the amount of information and number of choices increases.
Recommendation systems help users find items of interest of a particular type,
such as movies or restaurants, but are still somewhat awkward to use. Our
solution is to take advantage of the complementary strengths of personalized
recommendation systems and dialogue systems, creating personalized aides. We
present a system -- the Adaptive Place Advisor -- that treats item selection as
an interactive, conversational process, with the program inquiring about item
attributes and the user responding. Individual, long-term user preferences are
unobtrusively obtained in the course of normal recommendation dialogues and
used to direct future conversations with the same user. We present a novel user
model that influences both item search and the questions asked during a
conversation. We demonstrate the effectiveness of our system in significantly
reducing the time and number of interactions required to find a satisfactory
item, as compared to a control group of users interacting with a non-adaptive
version of the system
Annotation Graphs and Servers and Multi-Modal Resources: Infrastructure for Interdisciplinary Education, Research and Development
Annotation graphs and annotation servers offer infrastructure to support the
analysis of human language resources in the form of time-series data such as
text, audio and video. This paper outlines areas of common need among empirical
linguists and computational linguists. After reviewing examples of data and
tools used or under development for each of several areas, it proposes a common
framework for future tool development, data annotation and resource sharing
based upon annotation graphs and servers.Comment: 8 pages, 6 figure
Dialogue based interfaces for universal access.
Conversation provides an excellent means of communication for almost all people. Consequently, a conversational interface is an excellent mechanism for allowing people to interact with systems. Conversational systems are an active research area, but a wide range of systems can be developed with current technology. More sophisticated interfaces can take considerable effort, but simple interfaces can be developed quite rapidly. This paper gives an introduction to the current state of the art of conversational systems and interfaces. It describes a methodology for developing conversational interfaces and gives an example of an interface for a state benefits web site. The paper discusses how this interface could improve access for a wide range of people, and how further development of this interface would allow a larger range of people to use the system and give them more functionality
Development and Deployment of VoiceXML-Based Banking Applications
In recent times, the financial sector has become one of the most vibrant sectors of the Nigerian economy with about twenty five banks after the bank consolidation / merger
exercise. This sector presents huge business investments in the area of Information and Communication Technology (ICT). It is also plausible to say that the sector today is the
largest body of ICT services and products users.
It is no gainsaying the fact that so many Nigerians now carry mobile phones across the different parts of the country.
However, applications that provide voice access to real-time banking transactions from anywhere, anytime via telephone are still at their very low stage of adoption across the Nigerian banking and financial sector.
A versatile speech-enabled mobile banking application has been developed using VXML, PHP, Apache and MySQL. The developed application provides real-time access to
banking services, thus improving corporate bottom-line and Quality of Service (QoS) for customer satisfaction
ATLAS: A flexible and extensible architecture for linguistic annotation
We describe a formal model for annotating linguistic artifacts, from which we
derive an application programming interface (API) to a suite of tools for
manipulating these annotations. The abstract logical model provides for a range
of storage formats and promotes the reuse of tools that interact through this
API. We focus first on ``Annotation Graphs,'' a graph model for annotations on
linear signals (such as text and speech) indexed by intervals, for which
efficient database storage and querying techniques are applicable. We note how
a wide range of existing annotated corpora can be mapped to this annotation
graph model. This model is then generalized to encompass a wider variety of
linguistic ``signals,'' including both naturally occuring phenomena (as
recorded in images, video, multi-modal interactions, etc.), as well as the
derived resources that are increasingly important to the engineering of natural
language processing systems (such as word lists, dictionaries, aligned
bilingual corpora, etc.). We conclude with a review of the current efforts
towards implementing key pieces of this architecture.Comment: 8 pages, 9 figure
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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