Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees

Zhao Tuo; Zhao Yunxin; Chen Xin

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Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees

机译：使用语音决策树的随机森林对CD-DNN-HMM进行集成声学建模

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摘要

We propose a novel approach to generate an ensemble of context-dependent deep neural networks (CD-DNNs) by using random forests of phonetic decision trees (RF-PDTs) and construct an ensemble acoustic model (EAM) accordingly for speech recognition. We present evaluation results on the TIMIT dataset and a telemedicine automatic captioning dataset and demonstrate the superior performance of the proposed RF-PDT+CD-DNN based EAM over the conventional CD-DNN based single acoustic model (SAM) in phone and word recognition accuracies.

机译：我们提出了一种新方法，通过使用语音决策树（RF-PDTs）的随机森林来生成上下文相关的深度神经网络（CD-DNN）的集合，并相应地构建用于语音识别的集合声学模型（EAM）。我们在TIMIT数据集和远程医疗自动字幕数据集上展示评估结果，并展示了基于RF-PDT + CD-DNN的EAM在电话和单词识别精度方面优于基于传统CD-DNN的单一声学模型（SAM）的性能。

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来源
《Journal of VLSI signal processing systems for signal, image, and video technology》 |2016年第2期|187-196|共10页
作者
Zhao Tuo; Zhao Yunxin; Chen Xin;
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作者单位

Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA;

Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA;

Pearson Knowledge Technol, Menlo Pk, CA 94025 USA;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Ensemble acoustic model; Random forest; Phonetic decision tree; Deep neural network; Discriminative pre-training;

机译：集成声学模型随机森林语音决策树深度神经网络判别式预训练;

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专利

1. Random Forests of Phonetic Decision Trees for Acoustic Modeling in Conversational Speech Recognition [J] . Xue J., Zhao Y. IEEE transactions on audio, speech and language processing . 2008,第3期

机译：会话语音识别中语音建模的语音决策树随机森林
2. Head-cut gully erosion susceptibility modelling based on ensemble Random Forest with oblique decision trees in Fareghan watershed, Iran [J] . Quoc Bao Pham, Kaustuv Mukherjee, Akbar Norouzi, Geomatics,Natural Hazards & Risk . 2020,第1期

机译：基于Bealghan流域倾斜决策树的基于集合随机森林的头部沟壑腐蚀敏感性建模
3. Simultaneous Clustering of Phonetic Context, Dimension, and State Position for Acoustic Modeling Using Decision Trees [J] . Heiga Zen, Keiichi Tokuda, Tadashi Kitamura Systems and Computers in Japan . 2005,第14期

机译：使用决策树对语音上下文，维度和状态位置进行同时聚类以进行声学建模
4. Building an ensemble of CD-DNN-HMM acoustic model using random forests of phonetic decision trees [C] . Zhao Tuo, Zhao Yunxin, Chen Xin International Symposium on Chinese Spoken Language Processing . 2014

机译：使用语音决策树的随机森林建立CD-DNN-HMM声学模型的集合
5. Predicting Credit Union Customer Churn Behavior Using Decision Trees, Logistic Regression, and Random Forest Models [D] . Barr, Frederick. 2020

机译：使用决策树，逻辑回归和随机林模型预测信用联盟客户流失行为
6. Application of Random Forest Survival Models to Increase Generalizability of Decision Trees: A Case Study in Acute Myocardial Infarction [O] . Iman Yosefian, Ehsan Mosa Farkhani, Mohammad Reza Baneshi 2015

机译：随机森林生存模型在提高决策树通用性中的应用：以急性心肌梗死为例
7. CONSTRAINT INDUCTION OF PHONETIC-ACOUSTIC DECISION TREES FOR CROSSLINGUAL ACOUSTIC MODELLING [O] . 2008

机译：用于交叉声学建模的声 - 声决策树的约束诱导

Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees

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