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draft [2009/07/14 16:11] ptacek |
draft [2009/09/30 20:26] ptacek |
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- | ====== Description | + | ====== |
- | photopal domena, nahranej korpus, ze na to sou dafy (reusing SHEFF DM intergrated through Inamode Relayer (TID)) vhodny, moreover reusable for expected pomdp DM from UOX (reuse states, let pomdp' | + | The ASR module based on Hidden-Markov models transforms input speech into text, providing a front-end between |
- | typy odpovedi | + | to bridge the gap between dis-fluent spontaneous speech and a standard grammatical sentence. |
- | NLP server s tectomt, ASR/TTS/SR client, connected over network | + | |
- | XXX JPta | + | |
- | advances in Czech NLU (on reconstructed spoken data): 100vet(?) rucne anotovat pos, a-tree, t-tree, IE predicates, | + | The natural language understanding pipeline starts with part-of-speech tagging. Its result is passed |
- | pos ? analyzovat, generovat a kontrolovat ' | + | The Named Entity Recognition module marks personal names and geographical locations. |
- | ===== Speech Reconstruction ===== | ||
- | features: omit filler phrases, irrelevant speech events, false starts, repetitions, | ||
- | imlementation(zahrnout tuhle info?): moses natrenovany na korpusu | ||
- | performance indicator: BLEU score (overall scoring of all features) to annotated corpora from T5.2.1., nejaka baseline | ||
- | XXX Mirek | ||
- | ===== Morphology Analyzer | + | The Czech Companion follows the original idea of Reminiscing about the User's Photos, |
- | features: XXX Mirek/ | + | 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, |
- | performance indicator: accuracy | + | |
- | ===== Syntactic Parsing ===== | + | 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. |
- | features: induce dependencies and labels | + | |
- | performance indicator: f-measure | + | |
- | v tipu je natrenovat MacDonnalda na dialog datech, ten task je do M42, ze bysme | + | |
+ | 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 a common API. This eliminates the overhead of a repeated serialization and XML parsing that an Inamode based solution would impose otherwise. | ||
- | ===== Semantic Parsing ===== | + | The Knowledge Base consists of objects |
- | features: meaning representation with semantic roles (69 labels), coordinations, argument structure, partial ellipsis resolution, pronominal anaphora resolution, | + | |
- | performance indicator: f-measure | + | |
- | ===== Information Extraction ===== | ||
- | features: template based identification of predicates | ||
- | covering predicates from before-mentioned set of DAFs. | ||
- | performance indicator: accuracy | ||
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- | ===== Named Entities Recognition ===== | ||
- | features: detect person names, geographical locations (organizations jsou potreba?) | ||
- | performance indicator: f-measure | ||
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- | ===== Dialog Act Tagging ===== | ||
- | features: tagset derived from DAMSL-SWBD, DA is a key feature driving | ||
- | performance indicator: | ||
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- | ===== Sentiment Analysis ===== | ||
- | features: za tohle bych vydaval klasifikator, | ||
- | performance indicator: f-measure | ||
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- | ===== Complete System Evaluation ===== | ||
- | T5.2.7 tohle zminuje, nick webb to pro nas asi neudela | ||
- | performance indicator: pocet slov ve vypovedich uzivatele(? | ||
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- | ===== Dialog Manager ===== | ||
- | features: reply types, using (language independed) predicates (prakticky to znamena, ze pojmenuju testy na prechodech v dafech anglicky) | ||
- | performance indicator: rucni hodnoceni prijatelnosti akce | ||
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- | ===== Natural Language Generation ===== | ||
- | features: variations, underspecified input (dott format), emotional markup (natvrdo v dafech a templatech u hodnoticich vet) | ||
- | performance indicator: BLEU score |