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Algerian Modern Colloquial Arabic Speech Corpus (AMCASC): regional accents recognition within complex socio-linguistic environments

机译:阿尔及利亚现代口语阿拉伯语语料库(AMCASC):在复杂的社会语言环境中识别区域口音

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摘要

The Algerian linguistic situation is very intricate due to the ethnic, geographical and colonial occupation influences which have lead to a complex sociolinguistic environment. As a result of the contact between different languages and accents, the Algerian speech community has acquired a distinctive sociolinguistic situation. In addition to the intra- and inter- lingual variations describing day-to-day linguistic behavior of the Algerian speakers, their speech is characterized by the presence of many linguistic phenomena such as bilingualism and code switching. The study of automatic regional accent recognition in such a type of environment is a new idea in the field of automatic languages, dialect and accent recognition especially that previous studies were conducted using monolingual evaluation data. The assessment of the effectiveness of GMM-UBM and i-vectors frameworks for accent recognition approaches through the use of the Algerian Modern Colloquial Arabic Speech Corpus (AMCASC), which is a linguistic resource collected for this purpose, shows that not only the recording conditions mismatch, channels mismatch, recordings length mismatch and the amplitude clipping which have a non-desirable effect on the effectiveness of these acoustic approaches but also language contact phenomena are other perturbation sources which should be taken into consideration especially in real life applications .
机译:由于种族,地理和殖民地占领的影响,导致复杂的社会语言环境,阿尔及利亚的语言情况非常复杂。由于不同语言和口音之间的联系,阿尔及利亚语音社区已形成了独特的社会语言环境。除了描述阿尔及利亚人日常语言行为的内部和语言间差异之外,他们的语音还具有许多语言现象的特征,例如双语和代码转换。在这种类型的环境中,自动区域重音识别的研究是自动语言,方言和重音识别领域的一个新思想,特别是以前的研究是使用单语评估数据进行的。通过使用阿尔及利亚现代口语阿拉伯语语料库(AMCASC)来评估GMM-UBM和i-vector框架对口音识别方法的有效性,这是为此目的而收集的一种语言资源,它表明,不仅记录条件不匹配,通道不匹配,记录长度不匹配和幅度削波对这些声学方法的有效性产生不良影响,但语言接触现象也是其他扰动源,应特别考虑在现实生活中的应用。

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