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1 Spontaneous-Speech Dialogue System In Limited Domains (98 - 01) Development of an oral human-machine interface, by way of dialogue, for a semantically limited task: Queries into a database with information on Spanish trains Supported by CICYT(Comisión Interministerial de Ciencia y Tecnologia) of Spanish Government Project Overview (I)
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2 Partners list EHU (Universidad del Pais Vasco) UJI (Universidad Jaume I, Castellón) UPC-I (Universidad Politécnica de Cataluña) UPC-T (Universidad Politécnica de Cataluña) UPV (Universidad Politécnica de Valencia) UZ (Universidad de Zaragoza) Project: Spontaneous-Speech Dialogue System In Limited Domains (I)
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3 Project tasks (I) The acquisition of a corpus so as to study the dialogue in the task. A study on spontaneous speech and its modelling. The development of robust speech signal modelling techniques, to cope with variations due to speaker, background and channel effects. Project: Spontaneous-Speech Dialogue System In Limited Domains (II)
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4 Project tasks (II) The study and development of the dialogue system in the semantically restricted environment of the task The speech recognition module The understanding module The system that will generate an oral answer Project: Spontaneous-Speech Dialogue System In Limited Domains (III)
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5 Project tasks (III) The development of a prototype of the dialogue system for railway information in Spanish over the telephone network. Project: Spontaneous-Speech Dialogue System In Limited Domains (IV)
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6 Why the railway information task was chosen? -Delimited task. Easy to understand -Vocabulary stable. There are no foreign word (As in flights information or entertainment) -Rich conversations. Several turn-taking Project: Spontaneous-Speech Dialogue System In Limited Domains (V)
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7 Why the railway information task was chosen? -Delimited task. Easy to understand -Vocabulary stable. There are no foreign word (As in flights information or entertainment) -Rich conversations. Several turn-taking Project: Spontaneous-Speech Dialogue System In Limited Domains (VI)
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8 200 conversations from the RENFE call information centre. Calls from Barcelona. In Spanish. Selection of different ways of asking for information Language too complex Adquisition of the person-to-person corpus (I)
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9 Redefinition the task. Eliminating complexes Design of the Dialog Controller. Design of the Answer Generator Preparing the man-machine corpus Adquisition of the person-to-person corpus (II)
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10 People uses different when they talk to a machine The wizard of Oz strategy allows the obtaining examples before the systed is developed Adquisition of the man-machine corpus
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11 aTTemps (accès telefonic al Temps) aTTemps is an automatic system to access meteorological information by phone. Supported by Catalunya Government Universitat Politècnica de Catalunya Universitat de Barcelona Project Overview (II)
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12 Provides personalized real-time data on a set of meteorological conditions on each place of the Catalan geography In Catalan language Phone: 807 01 20 12 (in Spain). http://www.smc.gencat.es Project: aTTemps (accès telefonic al Temps)
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13 The Dialogue Manager Module in aTTemps (I) Main goals Provide the right information in minimum time Guiding the user in order to avoid situations where she will be lost
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14 The Dialogue Manager Module in aTTemps (II) Strategy Dialogue Flow. Barge-in Confirmation policy Implicit as a general rule Explicit in critical situations Amount of Data per Turn Considering the complexity Helping features. Helping messages Language generation Using templates
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15 System: Welcome to the ATTEMPS meteorological warning and information system. You can always say help, correction, repetition or exit. From which Catalan place do you want information, or do you want to establish a warning? User: I am interested in Barcelona, please. System: From Badalona, which information do you need? User: I want to correct, not from Badalona. System: From which Catalan place do you want information User: I want to know the weather right now in Barcelona. System: From Barcelona, which information do you need? User: I need the temperature, please. System: In the last measure at 14:30h, the temperature was 20 degrees. Do you need any other information User: No, thanks. System: Thanks for calling aTTemps : An example of conversation
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