Speaker Adaptation Using ICA-Based Feature Transformation
نویسندگان
چکیده
منابع مشابه
Phoneme recognition using ICA-based feature extraction and transformation
We investigate the use of independent component analysis (ICA) for speech feature extraction in speech recognition systems. Although initial research suggested that learning basis functions by ICA for encoding the speech signal in an e5cient manner improved recognition accuracy, we observe that this may be true for a recognition tasks with little training data. However, when compared in a large...
متن کاملAcoustic feature transformation using UBM-based LDA for speaker recognition
In state-of-the-art speaker recognition system, universal background model (UBM) plays a role of acoustic space division. Each Gaussian mixture of trained UBM represents one distinct acoustic region. The posterior probabilities of features belonging to each region are further used as core components of Baum-Welch statistics. Therefore, the quality of estimated Baum-Welch statistics depends high...
متن کاملRobust speaker identification using cross-correlation GTF-ICA feature
Robust feature for speaker identification in noisy environments is proposed. This method is inspired by the human binaural auditory system. A pair of microphones is used to replicate human ears in the processing. Crosscorrelation processing is taken of the microphone outputs after Gammatone bandpass filtering, rectification and compression. ICA is then applied to the real cepstrum of the correl...
متن کاملFeature Extraction Using ICA
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving better performances. In this paper, we propose a new feature extraction algorithm using independent component analysis (ICA) for classification problems. By using ICA in solving supervised classification problems, we ...
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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ETRI Journal
سال: 2002
ISSN: 1225-6463
DOI: 10.4218/etrij.02.0202.0003