巴斯克语语境下面向多语言语音识别的语言识别

N. Barroso, K. L. D. Ipiña, Odei Barroso, A. Ezeiza, Unai Susperregi
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引用次数: 2

摘要

自动语音识别(ASR)是一个广泛的研究领域,吸收了许多研究界的努力。强大的语音识别系统可以应用于家庭、办公室或企业的自动化,生产过程的监控,电话或电信服务的自动化。多语言大词汇连续语音识别系统的开发涉及语言识别、语音解码、语言建模和语言资源开发等问题。对多语言系统的兴趣引起了人们的兴趣,因为巴斯克地区有三种官方语言(巴斯克语、西班牙语和法语),尽管巴斯克语与其他两种语言的根源非常不同,但它们之间有很多语言互动。本文描述了一种面向巴斯克上下文的鲁棒多语言语音识别的语言识别(LID)系统的开发。这项工作提出了LID的混合策略,基于支持向量机和多层感知器分类器对系统元素的选择以及语音识别任务的随机方法(隐马尔可夫模型和n-grams)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Language identification oriented to Multilingual Speech Recognition in the Basque context
Automatic Speech Recognition (ASR) is a broad research area that absorbs many efforts from the research community. Robust speech recognition systems can be applied to automation of houses, office or business, monitoring of manufacturing processes, automation of telephone or telecommunication services. The development of Multilingual Large Vocabulary Continuous Speech Recognition systems involves issues as: Language Identification, Acoustic Phonetic Decoding, Language Modelling or the development of appropriated Language Resources. The interest on Multilingual Systems arouses because there are three official languages in the Basque Country (Basque, Spanish, and French), and there is much linguistic interaction among them, even if Basque has very different roots than the other two languages. This paper describes the development of a Language Identification (LID) system oriented to robust Multilingual Speech Recognition for the Basque context. The work presents hybrid strategies for LID, based on the selection of system elements by Support Vector Machines and Multilayer Perceptron classifiers and stochastic methods for speech recognition tasks (Hidden Markov Models and n-grams).
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