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In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine...
Automatic assessment of word stress error is an integral part for oral language grading system. However, problems that the property of vowels depends on its context information and the data sparseness of different vowel class are yet to be solved. This paper shall briefly introduce a hybrid method consisting of both traditional prosodic features and proposed context dependent strategies. In classification...
Prosody is an important factor for a high quality text-to- speech (TTS) system. Prosody is often described with a hierarchical structure. So the generation of the hierarchical prosody structure is very important both in the corpus building and the real-time text analysis, but the prosody labeling procedure is laborious and time consuming. In this paper, an automatic prosody boundary label system is...
Recently a new language model, the random forest language model (RFLM), has been proposed and shown encouraging results in speech recognition tasks. In this paper we applied the RFLM to language identification tasks. We proposed a shared backoff smoothing to deal with data sparseness problem. Experiments were conducted on a subset of NIST 2003 language recognition evaluation data. The RFLM obtained...
In this paper, we present a novel keyword spotting (KWS) method derived from traditional acoustic KWS. The advantage of this method is that it doesn't need any manually transcribed data to train the acoustic model, so it can be deployed fast for KWS task dealing with small languages and dialectal speech, which the traditional KWS systems can't handle because of the lack of training data. A prototype...
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