918 research outputs found
WEATHER FORECAST DATA SEMANTIC ANALYSIS IN F-LOGIC
This paper addresses the semantic analysis problem in a spoken dialog system developed for the domain of weather forecasts. The main goal of semantic analysis is to extract the meaning from the spoken utterances and to transform it into a domain database format. In this work a semantic database for the domain of weather forecasts is represented using the F-logic formalism. Semantic knowledge is captured through semantic categories a semantic dictionary using phrases and output templates. Procedures for semantic analysis of Croatian weather data combine parsing techniques for Croatian language and slot filling approach. Semantic analysis is conducted in three phases. In the first phase the main semantic category for the input utterance is determined. The lattices are used for hierarchical semantic relation representation and main category derivation. In the second phase semantic units are analyzed and knowledge slots in the database are filled. Since some slot values of input data are missing in the third phase, incomplete data is updated with missing values. All rules for semantic analysis are defined in the F-logic and implemented using the FLORA-2 system. The results of semantic analysis evaluation in terms of frame and slot error rates are presented
A Croatian Weather Domain Spoken Dialog System Prototype
Speech technologies and language technologies have been already in use in IT for a certain time. Because of their great impact and fast growth, it is necessary to introduce these technologies for Croatian language. In this paper we propose a solution for developing
a domain-oriented spoken dialog system for Croatian language. We have chosen a weather domain because it has limited vocabulary, it has easily accessible data and it is highly applicable. The Croatian weather dialog system provides information about weather in different
regions of Croatia. The modules of the spoken dialog system perform automatic word recognition, semantic analysis, dialog management, response generation and text-to-speech synthesis. This is a first attempt to develop such a system for Croatian language and some
new approaches are presented
Automatsko raspoznavanje hrvatskoga govora velikoga vokabulara
This paper presents procedures used for development of a Croatian large vocabulary automatic speech recognition system (LVASR). The proposed acoustic model is based on context-dependent triphone hidden Markov models and Croatian phonetic rules. Different acoustic and language models, developed using a large collection of Croatian speech, are discussed and compared. The paper proposes the best feature vectors and acoustic modeling procedures using which lowest word error rates for Croatian speech are achieved. In addition, Croatian language modeling procedures are evaluated and adopted for speaker independent spontaneous speech recognition. Presented experiments and results show that the proposed approach for automatic speech recognition using context-dependent acoustic modeling based on Croatian phonetic rules and a parameter tying procedure can be used for efļ¬cient Croatian large vocabulary speech recognition with word error rates below 5%.Älanak prikazuje postupke akustiÄkog i jeziÄnog modeliranja sustava za automatsko raspoznavanje hrvatskoga govora velikoga vokabulara. Predloženi akustiÄki modeli su zasnovani na kontekstno-ovisnim skrivenim Markovljevim modelima trifona i hrvatskim fonetskim pravilima. Na hrvatskome govoru prikupljenom u korpusu su ocjenjeni i usporeÄeni razliÄiti akustiÄki i jeziÄni modeli. U Älanku su usporeÄ eni i predloženi postupci za izraÄun vektora znaÄajki za akustiÄko modeliranje kao i sam pristup akustiÄkome modeliranju hrvatskoga govora s kojim je postignuta najmanja mjera pogreÅ”no raspoznatih rijeÄi. Predstavljeni su rezultati raspoznavanja spontanog hrvatskog govora neovisni o govorniku. Postignuti rezultati eksperimenata s mjerom pogreÅ”ke ispod 5% ukazuju na primjerenost predloženih postupaka za automatsko raspoznavanje hrvatskoga govora velikoga vokabulara pomoÄu vezanih kontekstnoovisnih akustiÄkih modela na osnovu hrvatskih fonetskih pravila
Voice Operated Information System in Slovak
Speech communication interfaces (SCI) are nowadays widely used in several domains. Automated spoken language human-computer interaction can replace human-human interaction if needed. Automatic speech recognition (ASR), a key technology of SCI, has been extensively studied during the past few decades. Most of present systems are based on statistical modeling, both at the acoustic and linguistic levels. Increased attention has been paid to speech recognition in adverse conditions recently, since noise-resistance has become one of the major bottlenecks for practical use of speech recognizers. Although many techniques have been developed, many challenges still have to be overcome before the ultimate goal -- creating machines capable of communicating with humans naturally -- can be achieved. In this paper we describe the research and development of the first Slovak spoken language dialogue system. The dialogue system is based on the DARPA Communicator architecture. The proposed system consists of the Galaxy hub and telephony, automatic speech recognition, text-to-speech, backend, transport and VoiceXML dialogue management modules. The SCI enables multi-user interaction in the Slovak language. Functionality of the SLDS is demonstrated and tested via two pilot applications, ``Weather forecast for Slovakia'' and ``Timetable of Slovak Railways''. The required information is retrieved from Internet resources in multi-user mode through PSTN, ISDN, GSM and/or VoIP network
End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions
End-to-end task-oriented dialogue (EToD) can directly generate responses in
an end-to-end fashion without modular training, which attracts escalating
popularity. The advancement of deep neural networks, especially the successful
use of large pre-trained models, has further led to significant progress in
EToD research in recent years. In this paper, we present a thorough review and
provide a unified perspective to summarize existing approaches as well as
recent trends to advance the development of EToD research. The contributions of
this paper can be summarized: (1) \textbf{\textit{First survey}}: to our
knowledge, we take the first step to present a thorough survey of this research
field; (2) \textbf{\textit{New taxonomy}}: we first introduce a unified
perspective for EToD, including (i) \textit{Modularly EToD} and (ii)
\textit{Fully EToD}; (3) \textbf{\textit{New Frontiers}}: we discuss some
potential frontier areas as well as the corresponding challenges, hoping to
spur breakthrough research in EToD field; (4) \textbf{\textit{Abundant
resources}}: we build a public website\footnote{We collect the related papers,
baseline projects, and leaderboards for the community at
\url{https://etods.net/}.}, where EToD researchers could directly access the
recent progress. We hope this work can serve as a thorough reference for the
EToD research community.Comment: Accepted at EMNLP202
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
This paper surveys the current state of the art in Natural Language
Generation (NLG), defined as the task of generating text or speech from
non-linguistic input. A survey of NLG is timely in view of the changes that the
field has undergone over the past decade or so, especially in relation to new
(usually data-driven) methods, as well as new applications of NLG technology.
This survey therefore aims to (a) give an up-to-date synthesis of research on
the core tasks in NLG and the architectures adopted in which such tasks are
organised; (b) highlight a number of relatively recent research topics that
have arisen partly as a result of growing synergies between NLG and other areas
of artificial intelligence; (c) draw attention to the challenges in NLG
evaluation, relating them to similar challenges faced in other areas of Natural
Language Processing, with an emphasis on different evaluation methods and the
relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118
pages, 8 figures, 1 tabl
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