Speaker adaptation by correlation (ABC)
نویسندگان
چکیده
This paper describes a new rapid speaker adaptation algorithm using a small amount of adaptation data. This algorithm, termed adaptation by correlation (ABC), exploits the intrinsic correlation among speech units to update the speech models. The algorithmupdates the means of each Gaussian based on its correlation with means of the Gaussians which are observed in the adaptation data; the updating formula is derived from the theory of least squares. Our experiments on the ARPA NAB-94 evaluation (Eval-94) and the ARPA Hub4-96 (Hub4-96) tasks indicate that ABC seems more stable than MLLR when the amount of data for adaptation is very small ( 5 seconds), and that ABC seems to enhance MLLR when they are combined.
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 کاملThe use of speaker correlation information for automatic speech recognition
This dissertation addresses the independence of observations assumption which is typically made by today’s automatic speech recognition systems. This assumption ignores within-speaker correlations which are known to exist. The assumption clearly damages the recognition ability of standard speaker independent systems, as can seen by the severe drop in performance exhibited by systems between the...
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 کاملInter-speaker correlations, intra-speaker correlations and Bayesian adaptation
There are two types of prior distribution that can be viewed as natural for extended MAP (or EMAP) speaker adaptation. One arises from modeling the correlations between speakers (assumed to be constant across HMM Gaussians) and the other from modeling the correlations between HMM Gaussians (assumed to be constant across speakers). In this paper we present new results establishing the usefulness...
متن کاملWhat is the best type of prior distribution for EMAP speaker adaptation?
There are two types of prior distribution that can be viewed as natural for extended MAP (or EMAP) speaker adaptation. One arises from modeling the correlations between speakers (assumed to be constant across HMM Gaussians) and the other from modeling the correlations between HMM Gaussians (assumed to be constant across speakers). In this paper we present new results establishing the usefulness...
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 1997