Segment-Based Acoustic Models for Continuous Speech Recognition

9408896奥斯滕多夫这是一个标准奖，作为根据IRI-8902124进行的研究的延伸，并由ARPA为科学和工程研究培训增强奖而举办的项目竞赛提供资金。这项研究旨在研究基于模型的方法，或通过倒谱和参数变换来表示信道噪声和失真，涉及一名研究生和一名本科生跟随先前奖项激励的研究主题。该奖项下的研究生研究考虑使用并行HMM和加性和卷积噪声的最大似然信道识别的基于模型的信道补偿的分段模型方法。本科生的研究主题包括评估用于噪声和通道补偿的信号处理方法，因为它们与使用标准Melwarted倒谱和导数特征的更经典的方法进行比较。这两个项目都补充了最初奖项的目标，并扩大了目标。

9408896 Ostendorf This is a standard award made as an extension to the research conducted under IRI-8902124 and is funded under ARPA's program competition for the Augmentation Awards for Science and Engineering Research Training. The research proposed investigates model-based approaches or the representation of channel noise and distortion via cepstrum and parametric transformations, involving one graduate and one undergraduate student following research topic stimulated by the previous award. Graduate student research under this award considers a segmental model approach to model-based channel compensation using parallel HMMs and maximum likelihood channel identification of both additive and convolutional noise. The undergraduate research topic involves the evaluation of signal processing approaches for noise and channel compensation as they compare with more classical approaches that use standard Melwarped cepstra and derivative features. Both of these projects complement the objective of the original award and augment it.