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We propose to detect mispronunciations in a language learners speech via a discriminatively trained DNN in the phonetic space. The posterior probabilities of “senones” populated in a decision tree are trained and predicted speaker independently. Acoustic features of each input segment (with preceding and succeeding contexts of several frames) are mapped unto the whole set of senones in their corresponding...
The qualification rate of power system state estimation has become an important assessment indicator of power grid operation in regional power grid. In this paper, combined with the operation of the state estimation software in Hebei power grid, the influence factors of the state estimation's qualification rate is analyzed. The improvement measures to improve state estimation's qualification rate...
In this paper, we propose a Neural Network (NN) based, Logistic Regression (LR) classifier for improving phone mispronunciation detection rate in a Computer-Aided Language Learning (CALL) system. A general neural network with multiple hidden layers for extracting useful speech features is first trained with pooled, training data, and then phone-dependent, 2-class logistic regression classifiers are...
In this paper we investigate a Deep Neural Network (DNN) based approach to acoustic modeling of tonal language and assess its speech recognition performance with different features and modeling techniques. Mandarin Chinese, the most widely spoken tonal language, is chosen for testing the tone related ASR performance. Furthermore, the DNN-trained, tone-sensitive model is evaluated in automatic detection...
Deep Neural Network (DNN), which can model a long-span, intricate transform compactly with a deep-layered structure, has recently been investigated for parametric TTS synthesis with a fairly large corpus (33,000 utterances) [6]. In this paper, we examine DNN TTS synthesis with a moderate size corpus of 5 hours, which is more commonly used for parametric TTS training. DNN is used to map input text...
Automatic detection/prediction of pitch accent, which determines the existence of prominent syllable of a word and its corresponding pitch accent pattern, is crucial in making expressive Text-To-Speech (TTS) synthesis. To train a model to detect and predict pitch accent usually requires a large amount of annotated training data to be manually labeled by phonetically trained language experts, which...
Power cloud technology meets the need of smart grid, which is better in data processing, control technologies and strategies. With the construction of smart grid to speed up, security risks in power cloud can't be ignored. This paper begins with the hierarchy of power cloud, and then focuses on analyzing the potential security risks in power cloud construction. With the cloud security model, some...
The effect on distribution network with penetration of photovoltaic system is studied. Firstly, the effect to distribution network's power flow is studied when photovoltaic power is connected to distribution network. The bus voltages are calculated when the power factor cosφ of the photovoltaic power varies from -0.95 (absorbing reactive power) to +0.95 (developing reactive power) and photovoltaic...
With the development of power grid interconnection, the low frequency oscillation including local modes and inter-area modes is becoming more notable. And the effectiveness of local power system stabilizer (LPSS) in damping inter-area modes is not very well. Then the global PSS (GPSS) based on WAMS (wide area measurement system) is proposed which is aimed to damp inter-area modes. This paper summarizes...
With the development of power grid interconnection, the low frequency oscillation is becoming more and more prominent which threats the stability of the system. It consists of local modes and inter-area modes, and the effectiveness of local PSS in damping inter-area modes is limited. Then the global power system stabilizer (GPSS) based on WAMS (Wide Area Measurement System) is proposed. First 3 problems...
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