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- | ====== | + | ====== |
- | [[Progress Report]] | + | Czech Companion follows the original idea of Reminiscing about the User's Photos, |
+ | taking advantage of the data collected in the first phase of the project (using a Wizard-of-Oz setting). The full recorded corpora was transcribed, manual speech reconstruction was done on 92.6% of utterances((still in progress)) and a pilot dialog acts annotation was performed on sample of 1000 sentences. | ||
+ | The architecture is the same as in the English version, i.e. a set of modules communicating through the Inamode (TID) backbone. However, the set of modules is different, see Figure 1. Regarding the physical settings, the Czech version runs on two notebook computers connected by a local network. One serves as a Speech Client, running modules dealing with ASR, TTS and ECA; the other one as an NLP Server. | ||
- | ====== Description | + | The NLU pipeline, DM, and NLG modules at the NLP Server are implemented using a CU's own TectoMT platform that provides access to a single in-memory data representation through common API. This eliminates the overhead |
- | The Czech version | + | The Knowledge Base consists |
- | The dialog is driven by a dialog manager component by USFD (originally developed for the English Senior Companion prototype), we supply the transition network (DAFs). The selection is backed by (a) appropriateness for the type of dialog we aim for (the corpus reveals frequent reoccurring topics to be handled by DAFs) , (b) availability of mature package within time frame that allows for integration, | ||
- | Our DAFs covering selected topics contain not only Companion replies mined from the corpora, but also new human-authored assessments, | + | ====== Progress Report ====== |
- | {{user: | + | [[Progress Report]] |
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- | ===== Automatic Speech Recognition (WP 5.1)===== | + | |
- | features: improved language models, real-time speaker adaptation | + | |
- | performance indicator: WER | + | |
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- | ===== Speech Reconstruction (WP 5.2) ===== | + | |
- | features: omit filler phrases, remove irrelevant speech events, handle false starts, repetitions, | + | |
- | performance indicator: BLEU score between actual output and manually reconstructed sentences from corpora (T5.2.1), baseline: Moses with default settings | + | |
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- | ===== Morphology Analyzer and POS tagging (WP 5.2) ===== | + | |
- | features: coverage of photo-pal domain, domain adapted tagger | + | |
- | performance indicator: OOV rate, accuracy | + | |
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- | ===== Syntactic Parsing (WP 5.2) ===== | + | |
- | features: induce dependencies and labels | + | |
- | performance indicator: accuracy (correctly induced edges, labels) | + | |
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- | ===== Semantic Parsing (WP 5.2) ===== | + | |
- | features: assignment of semantic roles (69 roles), coordinations, | + | |
- | performance indicator: accuracy (correctly induced edges, labels) | + | |
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- | ===== Information Extraction (WP 5.2) ===== | + | |
- | features: template based identification of predicates | + | |
- | covering predicates from before-mentioned set of DAFs. | + | |
- | performance indicator: accuracy | + | |
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- | ===== Named Entities Recognition (WP 5.2) ===== | + | |
- | features: detect person names, geographical locations, organization names | + | |
- | performance indicator: f-measure | + | |
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- | ===== Dialog Act Tagging (WP 5.2) ===== | + | |
- | features: domain tailored tag-set (variation of DAMSL-SWBD) | + | |
- | performance indicator: accuracy | + | |
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- | ===== Dialog Manager (WP 5.3) ===== | + | |
- | features: integrated DAF-based dialog manager from previous English prototype, | + | |
- | manual creation of DAFs covering following topics: Person_retired, | + | |
- | performance indicator: acceptability - manual evaluation of actions selected by DM | + | |
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- | ===== Natural Language Generation (WP 5.4) ===== | + | |
- | features: adding of functional words, morphological adjustments, | + | |
- | performance indicator: BLEU score | + | |
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- | ===== Emotional TTS (WP 5.5) ===== | + | |
- | features: emotions will be expressed implicitly, through the usage of communicative functions; new female voice database was recorded for this purposes | + | |
- | performance indicator: listening tests | + | |
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- | ===== Emotional Avatar Integration (WP 5.5) ===== | + | |
- | features: new Czech female voice with affective features will be integrated with the TID avatar | + | |
- | performance indicator: subjective evaluation of the naturalness and the ability | + | |
+ | [[http:// | ||
====== Scenario Brief ====== | ====== Scenario Brief ====== | ||
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C Podíváme se na další fotku? | C Podíváme se na další fotku? | ||
+ | ====== Scenario Brief 2 ====== | ||
+ | |||
+ | C1 Dobrý den, jak se jmenujete? intro | ||
+ | H1 Jindra. | ||
+ | |||
+ | C2 Já jsem Pavla a budu si s Vámi povídat o Vašich fotkách. intro | ||
+ | C2 Hned se můžeme podívat na první. photo_maintenance | ||
+ | C2 Co je na téhle fotce? | ||
+ | H2 Tak to je moje dcerka Jana, když se narodila. Ta je druhá, staršího jsem měla chlapce Jirku. Jana měla nevyvinutý | ||
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+ | C3 A dneska je z ní pěkná mladá slečna. komentující věta | ||
+ | C3 Kdy se Jana narodila ? ask_on_detail | ||
+ | H3 Jana se narodila v roce 1957. To už jsem neměla ani tatínka. | ||
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+ | C4 To mě mrzí. hodnotící_obecná | ||
+ | H4 Tatínek zemřel v roce 1956 a Jana se potom narodila v červnu 1957. Dneska už je to máma od dvou dospělých děvčat. | ||
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+ | C5 Kolik vnoučat vlastně máte? | ||
+ | H5 Vnoučat mám teďka pět, Jirka má dva kluky a nyní, na staré kolena, holčičku. | ||
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+ | C6 A co vlastně dělá váš syn? ask_on_detail dafclovek_30, | ||
+ | H6 Můj syn je teďka v hospodě. | ||
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+ | C7 Takže Jirka je nyní v hospodě? repeat_rephrase | ||
+ | H7 Na staré kolena, vždyť už je mu taky 52, si vzal na starost hospodu. | ||
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+ | C8 To je ale šikovný. hodnotící_zacílená topic: | ||
+ | C8 A kde pracuje Jana? skip_to_associated_topic daf: | ||
+ | H8 Je lékařka a dělá tady v Plzni. | ||
+ | H8 Je ředitelka v kojeneckém ústavu. | ||
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+ | C9 Bydlí v Plzni? ask_on_detail daf: | ||
+ | H9 Ano, v Plzni. Jsou tady kousíček, na Klatovské třídě. | ||
+ | |||
+ | C10 Vzpomínáte si u téhle fotky ještě na něco? ask_for_more | ||
+ | H10 Už je to asi vše. | ||
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+ | C Tak se podíváme na další snímek. | ||
+ | C Co na něm můžeme vidět? | ||
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+ | ====== Scenario Brief 3 ====== | ||
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+ | C1 Dobrý den Marie, už jsem se těšila na Vaše další fotky. intro, na základě loginu | ||
+ | C1 Co na té první můžeme vidět? | ||
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+ | H1 To jsme byli prvně s novým autem na Šumavě. | ||
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+ | H1 Sice trochu pršelo, ale na lyže se muselo. | ||
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+ | C2 Jak často jste na Šumavu jezdili? | ||
+ | | ||
+ | H2 Dost, ne tak často, ale aspoň asi dvakrát, třikrát za zimu. | ||
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+ | C3 Jezdili jste jenom na lyže? | ||
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+ | H3 Byli jsme se tam podívat na chaloupku pana Wericha a také jsme byli v kostele. | ||
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+ | H3 Kostel byl plný lidu, což u nás ve Štěnovicích není. | ||
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+ | C4 To je zajímavé. | ||
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+ | H4 Já jsem sice z Útušic, ale chodíme do kostela do Štěnovic. | ||
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+ | H4 Spadáme tam jak k doktoru, tak i pod matriku. | ||
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+ | C5 Rozumím. | ||
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+ | C5 Jezdili jste i na víc dní, nebo jen na jednodenní výlety? | ||
+ | | ||
+ | H5 S dětmi, když byly malé, to byly jednodenní výlety. | ||
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+ | C6 Lyžujete ráda? | ||
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+ | H6 Lyžovala jsem, ale teď už vůbec ne, protože mám operované koleno i kyčel. | ||
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+ | C7 Člověk už na sebe musí dávat víc pozor. | ||
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+ | C7 Máte to na Šumavu daleko? ask_on_detail daf:vylet | ||
+ | H7 Je to od nás z Útušic přes 30 kilometrů. | ||
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+ | C8 Takže jste jezdili na Šumavu na lyže autem. | ||
+ | C8 Děti také baví lyžovat? skip_to_associated_topic | ||
+ | H8 Syn rád jezdí na běžkách. A dnes je moderní ten snowboard, tak to zkouší. | ||
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+ | C9 To je šikovný. hodnotící_zacílená | ||
+ | C9 A dcera? ask_on_detail | ||
+ | H9 Ta moc nesportuje. | ||
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+ | C Řeknete mi ještě něco k téhle fotce? ask_for_more | ||
+ | C A kdo je na téhle? photo_maintenance | ||