Affine Transformations in Speaker Adaptation – Why Simpler Is Better
نویسندگان
چکیده
Speaker adaptation is an important technique that can compensate for the mismatch between training data and the vocal characteristics of an individual user in a speech recognition system, however this can come at the cost of increased computational complexity. This paper reports a detailed comparison of four different affine transformation configurations for speaker adaptation, and the evaluation of their recognition accuracy, complexity and memory requirements. Results of this comparison show that for optimum parameter choices, simpler transformation configurations are capable of producing accuracies close to those of the conventional full transformation, allowing the computational complexity to be reduced by one to two orders of magnitude.
منابع مشابه
Speaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
متن کاملSpeaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
متن کاملStudies in transformation-based adaptation
This paper studies the use of transformation-based speaker adaptation in improving the performance of large vocabulary continuous speech recognition systems. We present a formulation of the adaptation procedure that is simpler than existing methods. Our experiments demonstrate that speaker normalization continues to be important even after signi cant amounts of speaker adaptation. An automatic ...
متن کاملAdaptation of a tongue shape model by local feature transformations
Reconstructing the full contour of the tongue from the position of 3 to 4 landmarks on it is useful in articulatory speech work. This can be done with submillimetric accuracy using nonlinear predictive mappings trained on hundreds or thousands of contours extracted from ultrasound images. Collecting and segmenting this amount of data from a speaker is difficult, so a more practical solution is ...
متن کاملFast adaptation using constrained affine transformations with hierarchical priors
In this paper we present an approach to transformation based model adaptation that combines a fast, closed form solution to the MAP estimation of our transforms with robust priors. The robust priors are found using the technique of hierarchical priors, and a closed form solution is achieved by choosing diagonally constrained affine transformations and a suitable family of prior distributions fo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002