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LOW-RESOURCE LANGUAGE RECOGNITION USING A FUSION OF PHONEME POSTERIORGRAM COUNTS, ACOUSTIC AND GLOTTAL-BASED I-VECTORS

机译：使用pHONEmE后现代数据，声学和基于光学的I-向量的融合进行低资源语言识别

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L. F. D’haro; R. Cordoba; M. A. Caraballo; J. M. Pardo;
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年度 2013
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1. Phoneme Set Design Based on Integrated Acoustic and Linguistic Features for Second Language Speech Recognition [J] . Xiaoyun WANG, Tsuneo KATO, Seiichi YAMAMOTO IEICE transactions on information and systems . 2017,第4期

机译：基于语音和语言特性的音素集设计用于第二语言语音识别
2. Acoustic Analysis of Intensive Language Exposure on Second Language Learners’ Cognitive Perception Pattern of American English Phonemes [J] . Chunyi Zhou NeuroQuantology: an interdisciplinary journal of neuroscience and quantum physics . 2018,第4期

机译：强化语言暴露对美国英语音素第二语言学习者认知知觉模式的声学分析
3. Integrating Language Independent Segmentation and Language Dependent Phoneme Based Modeling for Tamil Speech Recognition System [J] . S Saraswathi, T.V. Geetha, K. Saravanan Asian Journal of Information Technology . 2006,第1期

机译：基于语言独立分割和基于语言的音素集成的泰米尔语语音识别系统建模
4. Low-resource language recognition using a fusion of phoneme posteriorgram counts, acoustic and glottal-based i-vectors [C] . DHaro L.F., Cordoba R., Caraballo M.A., IEEE International Conference on Acoustics, Speech and Signal Processing . 2013

机译：使用音素后序计数，基于声学和声门的i-vector进行融合的低资源语言识别
5. Automatic Speech Recognition for Low-Resource and Morphologically Complex Languages [D] . Morris, Ethan. 2021

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6. Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features bypassing the phoneme as recognition unit [O] . Denis Arnold, Fabian Tomaschek, Konstantin Sering, -1

机译：通过错误驱动的学习算法可以区分自发会话语音中的单词其准确性与人类类似可以从智能声学特征中区分出含义而绕过音素作为识别单元
7. Low-resource language recognition using a fusion of phoneme posteriorgram counts, acoustic and glottal-based i-vectors [O] . Dharo Enríquez Luis Fernando, Córdoba Herralde Ricardo de, Caraballo Morcillo Miguel Ángel, 2013

机译：使用音素后序计数，基于声学和声门的i-vector进行融合的低资源语言识别

LOW-RESOURCE LANGUAGE RECOGNITION USING A FUSION OF PHONEME POSTERIORGRAM COUNTS, ACOUSTIC AND GLOTTAL-BASED I-VECTORS

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