1,721,170 research outputs found
SLIM prosodic automatic tools for self-learning instruction
No full textWe present the Prosodic Module of a courseware for computer-assisted foreign language learning called SLIM ± an
acronym for Multimedia Interactive Linguistic Software, developed at the University of Venice (see Delmonte et al.,
1999a,b). The Prosodic Module has been created in order to deal with the problem of improving a student's performance
both in the perception and production of prosodic aspects of spoken language activities. It is composed of two di erent
sets of Learning Activities, the ®rst one dealing with phonetic and prosodic problems at word level and at segmental level
± where segmental refers to syllable-sized segments; the second one dealing with prosodic aspects at phonological phrase
and utterance suprasegmental level. The main goal of Prosodic Activities is to ensure consistent and pedagogically sound
feedback to the student intending to improve his/her pronunciation in a foreign language. We argue that the use of
Automatic Speech Recognition (ASR) as Teaching Aid should be under-utilized and should be targeted to narrowly
focussed spoken exercises, disallowing open-ended dialogues, in order to ensure consistency of evaluation. In addition,
we argue that ASR alone cannot be used to gauge Goodness of Pronunciation (GOP), being inherently inadequate for
that goal. On the contrary, we support the conjoined use of ASR technology and prosodic tools to produce GOP useable
for linguistically consistent and adequate feedback to the student
VEXTAL - Venezia per il Trattamento Automatico delle Lingue - Proceedings of the Conference
No full textINTERPRETING SPATIOTEMPORAL LOCATIONS
No full textGETARUNS, the system for text and reference understanding which is currently used for summarization and text generation has a highly sophisticated linguistically based semantic module which is used to build up the Discourse Model. Semantic processing is strongly modularized and distributed amongst a number of different submodules which take care of Spatio-Temporal Reasoning, Discourse Level Anaphora Resolution, and other subsidiary processes like Topic Hierarchy which cooperate when creating semantic individuals. These are then asserted in the Discourse Model (hence the DM), which is then the sole knowledge structure for the reasoning processes which is used to answer linguistically advanced queries on “when” and “where”. A version of the system runs under web
Evaluating Students' Summaries with GETARUNS
No full textEvaluating summaries is currently performed by the use of statistically-based tools which lack any linguistic knowledge and are unable to produce grammatical and semantic judgements (Landauer et al., 1997). However, summary evaluation needs precise linguistic information with a much finer-grained coverage than what is being offered by currently available statistically based systems. We assume that the starting point of any interesting application in these fields must necessarily be a good syntactic-semantic parser. In this paper we present the system for text understanding called GETARUNS, General Text and Reference Understanding System (Delmonte, 2003). The heart of the system is a rule-based top-down parser, which uses an LFG oriented grammar organization. Lately, a less constrained version of the parser for the application field of text summarization has been developed, which allows the system to recover gracefully from failures. To this end, the parser is couple with another concurrent parsing processes: a partial or shallow parse is always produced and used to recover from complete failures. GETARUNS, has a highly sophisticated linguistically based semantic module which is used to build up the Discourse Model. Semantic processing is strongly modularized and distributed amongst a number of different submodules which take care of Spatio-Temporal Reasoning, Discourse Level Anaphora Resolution. Evaluation taps information from the Discourse Model and uses Predicate Argument Structures (PAS) to detect students’ understanding of the text to summarize. It also uses the output of the Anaphora Resolution Module to check for most relevant topics in the text which the student should have addressed in his/her summary. The system uses a Topics-Stack while processing the text in order to corefer referential expressions: The Topic-Stack Hierarchy gauges nominal heads as either Main, Secondary or Potential Topic. This grading is used as a score that allows the system to detect the most relevant entities in the text at the end of the computation
Knowledge-poor and Knowledge-rich Approach in Anaphora Resolution Algorithms : a Comparison
Full text linkWe present an evaluation of three anaphora resolution algorithms – GuiTAR, JavaRAP and MARS – based on a subpart of the Susanne Corpus. The results were then compared to the GETARUNS system developed at Department of Language Sciences, Università Ca’ Foscari, Venezia, by prof. Delmonte. Our aim was to highlight differences between the systems and to see if knowledge-poor approach- es are suitable for AR, as they are much less labour-intensive and time-consum- ing than knowledge-rich systems
Parsing Difficulties and Phonological Processing in Italian
No full textA recognition grammar to supply information to a text-to-speech system for the synthesis of Italian must rely heavily upon lexical information, in order to instantiate the appropriate
grammatical relations.
Italian is an almost free word order language which nonetheless adopts fairly analyzable strategies to move major constituents: some of these can strongly affect the functioning of the phonological
component. Two basic claims will be made: i. difficulties in associating grammatical functions to constituent structure can be overcome only if Lexical Theory is adopted as a general theoretical framework, and translated into adequate computational formalisms like ATN or CHART;
i i . decisions made at previous point affect focus structure construal rules, which are higher level phonological rules which individuate intonation centre, build up adequate Intonational Groups and assign pauses to adequate sites, all being very sensitive to syntactic and semantic information.
We will concentrate on Subject/Object function association to c-structure in Italian, and its relation to ATN formalism, in particular HOLD mechanism and FlaGging. Then we will show how syntactic
decisions interact with an intonation grammar. We shall also introduce two functional notions:
STRUCTURE REVERSIBILITY vs. FUNCTIONAL REVERSIBILITY in Italian
Le parlate romagnole di confine: Analisi fonetica e fonologica
No full textPer parlate romagnole di confine intendiamo quelle varietà del dialetto romagnolo che si parlano al di sotto della linea La Spezia-Rimini; in particolare, come si può rilevare dalla carta geografica annessa, esse sono delimitate dal fiume Marecchia a Nord, dall'alta valle del Marecchia e del Savio nell'interno, sino a congiungersi con la giogaia appenninica al Passo dei Mandrioli. A Sud il confine coincide nettamente con il corso del Foglia e più ad Ovest con l'alta valle tiberina che si estende nell'aretino, quindi con le Marche, l'Umbria e la Toscana. Queste parlate mostrano caratteri che potremmo definire di transiziione tra i dialetti gallo-italici e quelli centro-meridionali; esse possiedono cioè dei tratti tipici del Nord, quali la palatalizzazione di A, l'apocope delle vocali atone finali; alcuni tratti tipici del dialetto romagnolo quali la sincope delle vocali mediane, un forte accento di parola, l'esistenza di o e di u centrali derivati da dittonghi secondari quindi assolutamente diversi da oe e da ue romanze; alcuni tratti di conservazione umbro-toscani, quali la mancata lenizione delle occlusive sorde, la mancata spirantizzazione delle palatali, la mancanza quasi completa di dittonghi cosiddetti "spontanei" tipici del romagnolo centrale e del Nord, nonché la presenza in questa zona di dittonghi dovuti alla ritrazione di accento, del tipo di ìa e ùa
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