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Apparatus and method for large vocabulary continuous speech recognition

机译:大词汇量连续语音识别的装置和方法

摘要

Provided is an apparatus for large vocabulary continuous speech recognition (LVCSR) based on a context-dependent deep neural network hidden Markov model (CD-DNN-HMM) algorithm. The apparatus may include an extractor configured to extract acoustic model-state level information corresponding to an input speech signal from a training data model set using at least one of a first feature vector based on a gammatone filterbank signal analysis algorithm and a second feature vector based on a bottleneck algorithm, and a speech recognizer configured to provide a result of recognizing the input speech signal based on the extracted acoustic model-state level information.
机译:提供了一种基于上下文相关的深度神经网络隐马尔可夫模型(CD-DNN-HMM)算法的大词汇量连续语音识别(LVCSR)设备。该装置可以包括提取器,其被配置为使用基于伽马通滤波器组信号分析算法的第一特征向量和基于第二特征向量的至少一个,从训练数据模型集中提取与输入语音信号相对应的声学模型状态水平信息。语音识别器被配置为基于瓶颈算法,并且语音识别器被配置为基于提取的声学模型状态水平信息来提供识别输入语音信号的结果。

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