DE eng

Search in the Catalogues and Directories

Page: 1 2 3 4 5...67
Hits 1 – 20 of 1.335

1
Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
BASE
Show details
2
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
BASE
Show details
3
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
BASE
Show details
4
Formalization of AMR Inference via Hybrid Logic Tableaux ...
Goldner, Eli Tecumseh. - : Brandeis University, 2022
BASE
Show details
5
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
BASE
Show details
6
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
BASE
Show details
7
10D: Phonology, Morphology and Word Segmentation #1 ...
BASE
Show details
8
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
BASE
Show details
9
19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 2 ...
BASE
Show details
10
18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 1 ...
BASE
Show details
11
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
Abstract: The primary goals of computer-assisted pronunciation training (CAPT) systems are to provide a personalized interactive environment and to accurately diagnose mispronunciations. Automatic speech recognition (ASR) systems have been shown to be an effective tool for diagnosing mispronunciations. While the data ASR systems output can be difficult for the layperson to understand, presenting it in a multimodal fashion can make it easier and feeding it into an automated narrative system can produce personalized feedback. In the absence of native speech examples, synthetic examples produced by text-to-speech (TTS) engines have proven to be an adequate substitute, making data collection easier and allowing for larger CAPT systems. In this work we present the SpeakEasy pronunciation trainer, a CAPT system that leverages ASR, TTS, automated narrative systems, and multimodal data representation to provide a personalized interactive environment that tracks a user's progress over time. ...
Keyword: Cognitive Linguistics; Cognitive Science; Computational Intelligence; Computational Linguistics; E-Learning; Phonetics; Phonology; Semantics
URL: https://dx.doi.org/10.48448/aa25-n461
https://underline.io/lecture/26896-speakeasy-pronunciation-trainer-personalized-multimodal-pronunciation-training
BASE
Hide details
12
The Match-Extend Serialization Algorithm in Multiprecedence ...
BASE
Show details
13
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
BASE
Show details
14
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
BASE
Show details
15
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
BASE
Show details
16
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
BASE
Show details
17
Including Signed Languages in Natural Language Processing ...
BASE
Show details
18
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
BASE
Show details
19
The Reading Machine: a Versatile Framework for Studying Incremental Parsing Strategies ...
BASE
Show details
20
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
BASE
Show details

Page: 1 2 3 4 5...67

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
1.335
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern