000 05365nam a22005295i 4500
001 978-3-031-40498-6
003 DE-He213
005 20240730181403.0
007 cr nn 008mamaa
008 230804s2023 sz | s |||| 0|eng d
020 _a9783031404986
_9978-3-031-40498-6
024 7 _a10.1007/978-3-031-40498-6
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aText, Speech, and Dialogue
_h[electronic resource] :
_b26th International Conference, TSD 2023, Pilsen, Czech Republic, September 4-6, 2023, Proceedings /
_cedited by Kamil Ekštein, František Pártl, Miloslav Konopík.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXXX, 362 p. 71 illus., 67 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14102
505 0 _aText: Japanese How-to Tip Machine Reading Comprehension by Multi-task Learning based on Generative Model -- One model to rule them all: ranking Slovene summarizers -- Searching for Reasons of Transformers' Success: Memorization vs Generalization -- A Dataset and Strong Baselines for Classification of Czech News Texts -- Resolving Hungarian Anaphora with ChatGPT -- Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines -- ParaDiom - A Parallel Corpus of Idiomatic Texts -- Measuring Sentiment Bias in Machine Translation -- Mono- and multilingual GPT-3 models for Hungarian -- The Unbearable Lightness of Morph Classification -- A German Parallel Clausal Coordinate Ellipsis Corpus that Aligns Sentences from the TüBa-D/Z Treebank with Reconstructed Canonical Forms -- Speech: Identifying Subjects Wearing a Mask from the Speech by Means of Encoded Speech Representations -- Impact of Including Pathological Speech in Pre-Training on Pathology Detection -- Morphological Tagging and Lemmatization of Spoken Corpora of Czech -- HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics -- Online Speaker Diarization Using Optimized SE-ResNet Architecture -- CML-TTS: A Multilingual Dataset for Speech Synthesis in Low-Resource Languages (Speech (in general), Corpora and Language Resources, Spe -- Developing State-of-the-Art End-to-End ASR for Norwegian -- VITS: Quality vs. Speed Analysis -- When Whisper Meets TTS: Domain Adaptation Using Only Synthetic Speech Data -- Unsupervised Learning for Automatic Speech Recognition In Air Traffic Control Environment -- The Effect of Human-Likeliness in French Robot-Directed Speech: A Study of Speech Rate and Fluency -- An online diarization approach for streaming applications based on tree-clustering and Bayesian resegmentation -- Evaluation ofSpeech Representations for MOS prediction -- Unified Modeling of Multi-Domain Multi-Device ASR Systems -- Voice Cloning for Voice Disorders: Impact of Phonetic Content -- Towards End-to-end Speech-to-text Summarization -- Multilingual TTS Accent Impressions for Accented ASR -- Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak -- Automatic Pronunciation Assessment of Non-native English based on Phonological Analysis -- Language Generalization using Active Learning in the context of Parkinson's Disease Classification.
520 _aThis book constitutes the refereed proceedings of the 26th International Conference on Text, Speech, and Dialogue, TSD 2023, held in Pilsen, Czech Republic, during September 4-6, 2023. The 31 full papers presented together with the abstracts of 3 keynote talks were carefully reviewed and selected from 64 submissions. The conference attracts researchers not only from Central and Eastern Europe but also from other parts of the world. One of its goals has always been bringing together NLP researchers with various interests from different parts of the world and promoting their cooperation. One of the ambitions of the conference is, not only to deal with dialogue systems but also to improve dialogue among researchers in areas of NLP, i.e., among the "text" and the "speech" and the "dialogue" people.
650 0 _aArtificial intelligence.
_93407
650 1 4 _aArtificial Intelligence.
_93407
700 1 _aEkštein, Kamil.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9124647
700 1 _aPártl, František.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9124648
700 1 _aKonopík, Miloslav.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9124649
710 2 _aSpringerLink (Online service)
_9124650
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031404979
776 0 8 _iPrinted edition:
_z9783031404993
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14102
_9124651
856 4 0 _uhttps://doi.org/10.1007/978-3-031-40498-6
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c90867
_d90867