Building on previous works (e.g. Kubozono 2006, and Kang 2010), this article attempts to establish a taxonomy for loanword prosody, referring specifically to the patterns of stress, tone, or pitch-accent that are found in loanwords. Toward a taxonomy, we consider the following factors: (i) whether the pronunciation of the word in the source language influences the assignment of prosody in the b...

(3) The Spoken Language Group at MIT's Laboratory for Computer Science also reported results for both the RM and ATIS SPREC test material [3]. The MIT SUMMIT system is a "segment-based" speech recognition system, including a front end that incorporates a model of the auditory system, a hierarchical segmentation algorithm to identify a network of possible acoustical segments, segmental measureme...

Cross-linguistic comparison is a good starting point for computer-assisted pronunciation training (CAPT). A comparison between the segment inventories of a learner’s mother tongue (L1) and the target language (L2) can be made on the basis of the IPA categories. Since these are claimed to reflect universal phonemic distinctions, mastering the contrasts in the target language in perception and pr...

Abstract Chinese word embeddings have recently garnered considerable attention. characters and their sub-character components, which contain rich semantic information, are incorporated to learn embeddings. can represent a combination of meaning, structure, pronunciation. However, existing embedding learning methods focus on the structure meaning characters. In this study, we aim develop an meth...

One of the challenges in automatic speech recognition is how to handle pronunciation variation. The main causes for pronunciation variation are the speaker (voice characteristics, accent, non-nativeness etc.) and the speaking style (reading, spontaneous responses, conversation etc.). An ASR system has basically two options for modelling the variation on the word and sub-word level: lexical mode...

For learning foreign language pronunciation, prosodic features are important as much as, or more than segmental features. For Japanese speakers, one of difficulties to learn English pronunciation is rhythm because of the differences between two languages: mora-timing rhythm and stress-timing rhythm. In order to correct errors in rhythm, the method of evaluating sentence stress that constitutes ...

The current study presents two meta-analyses to explore what underlies the assessment and teaching of comprehensible nativelike pronunciation among English-as-a-Second-Language speakers. In Study 1, listener studies (n = 37) were retrieved examining influence segmental, prosodic, temporal features on listeners’ intuitive judgements comprehensibility nativelikeness/accentedness as per different ...

Abstract:This study aims at describing learners’ features of pronunciation in terms the suprasegmental aspects found Jokowi’s Specch Lonjakan kasus Covid-19 dan penerapan PPKM Mikro on 23rdof June 2021. Suprasegmental information applies to several different linguistic phenomena such as pitch, duration, and loudness. Speech not only conveys question word or sentence, but also meaning behind eve...

Computer-assisted language learning (CALL) is reaching an up most position in the pedagogical field of English as a Second or Foreign Language (ESL/EFL). The present study was carried out to study the effect of using phonetic websites on Iranian EFL students’ pronunciation and knowledge of phonemic symbols. Participants of the study included 30 EFL female pre-intermediate students studyin...