scholarly journals Spoken Arabic News Classification Based on Speech Features

2017 ◽  
Vol V (VIII) ◽  
pp. 1478-1485
Author(s):  
Naser S. A. Abusulaiman
Keyword(s):  
Speech Features ◽  
Spoken Arabic

scholarly journals Performance vs. hardware requirements in state-of-the-art automatic speech recognition

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Alexandru-Lucian Georgescu ◽  
Alessandro Pappalardo ◽  
Horia Cucu ◽  
Michaela Blott
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
State Of The Art ◽  
Decision Makers ◽  
Computing Power ◽  
Trade Off ◽  
Speech Features ◽  
Commercial Applications ◽  
Guided Tour ◽  
Embedded Applications

AbstractThe last decade brought significant advances in automatic speech recognition (ASR) thanks to the evolution of deep learning methods. ASR systems evolved from pipeline-based systems, that modeled hand-crafted speech features with probabilistic frameworks and generated phone posteriors, to end-to-end (E2E) systems, that translate the raw waveform directly into words using one deep neural network (DNN). The transcription accuracy greatly increased, leading to ASR technology being integrated into many commercial applications. However, few of the existing ASR technologies are suitable for integration in embedded applications, due to their hard constrains related to computing power and memory usage. This overview paper serves as a guided tour through the recent literature on speech recognition and compares the most popular ASR implementations. The comparison emphasizes the trade-off between ASR performance and hardware requirements, to further serve decision makers in choosing the system which fits best their embedded application. To the best of our knowledge, this is the first study to provide this kind of trade-off analysis for state-of-the-art ASR systems.

Effect of aging on speech features and phoneme recognition: a study on Bengali voicing vowels

2012 ◽  
Vol 16 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Biswajit Das ◽  
Sandipan Mandal ◽  
Pabitra Mitra ◽  
Anupam Basu
Keyword(s):  
Phoneme Recognition ◽  
Speech Features

scholarly journals Augmenting Bug Localization with Part-of-Speech and Invocation

2017 ◽  
Vol 27 (06) ◽  
pp. 925-949 ◽  
Author(s):  
Yu Zhou ◽  
Yanxiang Tong ◽  
Taolue Chen ◽  
Jin Han
Keyword(s):  
Software Maintenance ◽  
Large Scale ◽  
Bug Localization ◽  
Bug Reports ◽  
Part Of Speech ◽  
Adaptive Technique ◽  
Bug Report ◽  
Software Maintenance And Evolution ◽  
Speech Features ◽  
Localization Approach

Bug localization represents one of the most expensive, as well as time-consuming, activities during software maintenance and evolution. To alleviate the workload of developers, numerous methods have been proposed to automate this process and narrow down the scope of reviewing buggy files. In this paper, we present a novel buggy source-file localization approach, using the information from both the bug reports and the source files. We leverage the part-of-speech features of bug reports and the invocation relationship among source files. We also integrate an adaptive technique to further optimize the performance of the approach. The adaptive technique discriminates Top 1 and Top N recommendations for a given bug report and consists of two modules. One module is to maximize the accuracy of the first recommended file, and the other one aims at improving the accuracy of the fixed defect file list. We evaluate our approach on six large-scale open source projects, i.e. ASpectJ, Eclipse, SWT, Zxing, Birt and Tomcat. Compared to the previous work, empirical results show that our approach can improve the overall prediction performance in all of these cases. Particularly, in terms of the Top 1 recommendation accuracy, our approach achieves an enhancement from 22.73% to 39.86% for ASpectJ, from 24.36% to 30.76% for Eclipse, from 31.63% to 46.94% for SWT, from 40% to 55% for ZXing, from 7.97% to 21.99% for Birt, and from 33.37% to 38.90% for Tomcat.

scholarly journals A qualitative analysis of perceptions of fluency in second language French

2016 ◽  
Vol 54 (2) ◽  
Author(s):  
Yvonne Préfontaine ◽  
Judit Kormos
Keyword(s):  
Second Language ◽  
Adult Learners ◽  
Qualitative Analysis ◽  
Quantitative Research ◽  
Qualitative Methodology ◽  
Quantitative Methods ◽  
Native Speaker ◽  
Cognitive Demand ◽  
Word Choice ◽  
Speech Features

AbstractIn the field of second language (L2) fluency, there is a common adherence to quantitative methods to examine characteristics and features of speech. This study extends the field by reporting on an investigation that analyzed native-speaker listeners’ perceptions of L2 fluency in French from a qualitative perspective. Three untrained judges rated students’ performance on speech tasks varying in cognitive demand and provided justifications for their perceptions of fluency. The goal of the research was to examine the factors that affect raters’ evaluations of fluency in response to three oral performances from 40 adult learners of French of varying proficiency. Qualitative analysis revealed that the main speech features that influenced native listeners’ perceptions of L2 fluency were speed, rhythm, pause phenomena, self-correction and efficiency/effortlessness in word choice, but also in target-like rhythm and prosody. The results of using such qualitative methodology highlights the important role that rhythm plays in fluency judgements in syllable-timed languages such as French, a factor which has not always been given much prominence in previous L2 fluency quantitative research.

Cross-dialectal variation in Arabic: Competing prestigious forms

1987 ◽  
Vol 16 (3) ◽  
pp. 359-367 ◽  
Author(s):  
Hassan R. Abd-El-Jawad
Keyword(s):  
Social Groups ◽  
Standard Variety ◽  
Adequate Description ◽  
Sociolinguistic Variation ◽  
Dialectal Variation ◽  
Standard Arabic ◽  
Arabic Sociolinguistics ◽  
Informal Settings ◽  
Spoken Arabic ◽  
Modern Standard

ABSTRACTMost researchers of Arabic sociolinguistics assume the existence of a sociolinguistic continuum with a local vernacular at the bottom and the standard variety at the top. Those researchers seem to equate the terms “prestige” and “standard”; consequently, they tend to consider Modern Standard Arabic (MSA) as the only prestige variety in all settings. This article presents evidence showing that if an adequate description of sociolinguistic variation of spoken Arabic is to be met, it is necessary to posit not only one standard speech variety, MSA, but also other prestigious local or regional varieties which act as local spoken standards competing with MSA in informal settings. It will be shown in the reported cases that in certain contexts speakers tend to switch from their local forms – though these latter may be identical to MSA – to other local features characteristic of other dominant social groups and that happen to be marked [–MSA], These local prestigious norms act like the standard spoken norms in informal settings. (Diglossic model, prestigious varieties, stereotypes, dominant social groups, competing standards, spoken Arabic).

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