Discriminative speaker adaptation using articulatory features
نویسندگان
چکیده
منابع مشابه
Discriminative speaker adaptation using articulatory features
This paper presents an automatic speech recognition system using acoustic models based on both sub-phonetic units and broad, phonological features such as Voiced and Round as output densities in a hidden Markov model framework. The aim of this work is to improve speech recognition performance particularly on conversational speech by using units other than phones as a basis for discrimination be...
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This paper presents a way to perform speaker adaptation for automatic speech recognition using the stream weights in a multi-stream setup, which included acoustic models for “Articulatory Features” such as ROUNDED or VOICED. We present supervised speaker adaptation experiments on a spontaneous speech task and compare the above stream-based approach to conventional approaches, in which the model...
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Articulatory Features (AF) have proven beneficial for Automatic Speech Recognition (ASR) in noisy environments, for hyper-articulated speech or in multi-lingual settings. A stream setup can combine standard sub-phone Gaussian Mixture Models with feature GMMs; the weights assigned to each feature stream such as VOICED or BILABIAL could intuitively be used for adaptation to speaker or text. In th...
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This paper describes a speaker verification system in which the talker and imposter models are adapted to achieve maximum discrimination, or equivalently minimum verification error. This goal is accomplishedby extending the minimum error classificationcriterion (MCE) and generalized probabilistic descent (GPD) algorithm to the task of adapting talker model parameters and the corresponding anti-...
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ژورنال
عنوان ژورنال: Speech Communication
سال: 2007
ISSN: 0167-6393
DOI: 10.1016/j.specom.2007.02.009