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Table of Contents
Progress Report
Hi Marc,
…
Re: progress: there is progress in the following:
- speech re-training for the collected dialogue data
- additional dialogue transription for ASR is ongoing (WP52.? T5.2.1)
- DM has been transferred from USFD to Prague (WP5.3)
being extensively tested
- DAF editor transfer is complete (WP5.3)
- Sample dialogues (specifically aimed at the demo)
are ready - issues are being resolved between CU/ZCU
- DAFs are being prepared for the SC-CZ scenario AND
the sample dialogues
- DA set is being prepared, also based on the sample dialogues (WP5.2)
- preliminary DA tagger working (WP5.2)
- integration work is ongoing (CU/ZCU, internally at CU)
but no functioning full demo yet
I hope this is OK for the progress report. Pavel (I.) might add more specifics regarding the ASR and especially TTS progress.
Best,
– Jan
Description of Czech Companion November Prototype
The Czech version of Companion deals with the Reminiscing about User's Photos scenario.
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's do the topology and handle the states transitions, post november work),
typy odpovedi a zpusob jejich implementace, rucne vyrobene dafy pro nasledujici topics: Person_Retired, Person_in_productive_age, Child, Husband, Wife, Wedding, Christmas, Handle_stalled_dialog
NLP server s tectomt, ASR/TTS/SR client, connected over network
XXX JPta
advances in Czech NLU (on reconstructed spoken data): 300-500vet(?) rucne anotovat pos, a-tree, t-tree, IE predicates, Named Entities, DA pro eval in-domain testy after Nov.
pos ? analyzovat, generovat a kontrolovat 'jen' kde je rozdil ve forme?
Speech Reconstruction
features: omit filler phrases, irrelevant speech events, false starts, repetitions, corrections, syntax smoothing (WO,
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 and POS tagging
features: XXX Mirek/Johanka
performance indicator: accuracy
Syntactic Parsing
features: induce dependencies and labels
performance indicator: f-measure
v tipu je natrenovat MacDonnalda na dialog datech, ten task je do M42, ted ne.
Semantic Parsing
features: meaning representation with semantic roles (69 roles), 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
Named Entities Recognition
features: detect person names, geographical locations (organizations myslim nepotrebne)
performance indicator: f-measure
Dialog Act Tagging
features: tagset derived from DAMSL-SWBD, DA is a key feature driving the decision, what to say next.
performance indicator: accuracy
Sentiment Analysis
features: za tohle bych vydaval klasifikator, co rozhoduje ,jestli se rekne 'To je smutné/veselé'. Tem adjektivum rucne priradim negative/positive sentiment.
performance indicator: f-measure
Complete System Evaluation
T5.2.7 tohle zminuje, nick webb to pro nas asi neudela
performance indicator: pocet slov ve vypovedich uzivatele(?),
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 vybrane akce
Natural Language Generation
features: variations, underspecified input (dott format), emotional markup (natvrdo v dafech a templatech u hodnoticich vet)
performance indicator: BLEU score