2009
DOI: 10.1007/s10772-010-9065-1
|View full text |Cite
|
Sign up to set email alerts
|

Prosodic tools for language learning

Abstract: In this paper we will be concerned with the role played by prosody in language learning and by the speech technology already available as commercial product or as prototype, capable to cope with the task of helping language learner in improving their knowledge of a second language from the prosodic point of view. The paper has been divided into two separate sections: Section One, dealing with Rhythm and all related topics; Section Two dealing with Intonation. In the Introduction we will argue that the use of A… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0

Year Published

2011
2011
2024
2024

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 13 publications
(8 citation statements)
references
References 31 publications
0
8
0
Order By: Relevance
“…ASR incorporating neural networks, probabilistic classifiers and decision making schemes, such as GMM, HMM and SVM, is one of the most effective technologies for CAPT design. Yet, some discrete precautions should be taken to apply ASR in a controlled CAPT environment [38]. A case in point is the unsuitability of ASR for automatic evaluation of learner input.…”
Section: Literature Reviewmentioning
confidence: 99%
“…ASR incorporating neural networks, probabilistic classifiers and decision making schemes, such as GMM, HMM and SVM, is one of the most effective technologies for CAPT design. Yet, some discrete precautions should be taken to apply ASR in a controlled CAPT environment [38]. A case in point is the unsuitability of ASR for automatic evaluation of learner input.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Computer-Assisted Prosody Teaching (CAPT) tools integrated with various speech processing technologies make it possible to obtain pitch plots so that to provide a visual representation of the speech. From a number of research works, we learn that, within L2 learning activities, training enhanced by such a visualization of pitch contours has a positive effect on learner's pronunciation (e. g., [9,10]). In particular, the authors of [11] conducted an interesting study, where they used speech analysis software (Praat) to present a visual display of the Chinese native speaker's pitch curves for learners, then asked learners to record themselves repeating the same words and compare their pitch contours with those of the native speaker.…”
Section: Capt Tools For Language Pronunciation Trainingmentioning
confidence: 99%
“…i.e. there is no need to refer to G. What (30) shows is that as N grows, the probability of getting previously unseen samples decreases linearly. Furthermore, the probability of the new sample to be equal to θ k is equal to (α 0 + N) −1 N k .…”
Section: Infinite Mixture Models and The Dirichlet Processesmentioning
confidence: 99%