This work presents the results in the analysis of the acoustic features (formants and the three suprasegmental features: tone, intensity and duration) of the vowel production in a group of 14 young speakers suffering different kinds of speech impairments due to physical and cognitive disorders. A corpus with unimpaired children’s speech is used to determine the reference values for these featur...

A general inductive Bayesian classification framework is introduced for data from multiple finite alphabets using predictive representations based on random urn models and generalized exchangeability. We develop a novel principle of generative supervised and semi-supervised probabilistic classification based on marginalizing simultaneous predictive classification probabilities for all test item...

This paper presents a new technique for the detection of short exons in DNA sequences. In this method, we analyze four DNA structural properties, which include the DNA bending stiffness, disrupt energy, free energy, and propeller twist, using the autoregressive (AR) model. The linear prediction matrices for the four features are combined to find the same set of linear prediction coefficients, f...

In recent years, corpus phonetics has become a rapidly expanding field. However, the lack of appropriate tools for automatic acoustic analysis hinders further development of the field. In this paper, we present a methodological study on the automatic extraction of vowel formants using both robust linear predictive coding (RLPC; Lee, 1988) and dynamic formant tracking (Talkin, 1987). Acoustic da...

In this paper, we investigate a new Bayesian predictive classi cation (BPC) approach to realize robust speech recognition when there exist mismatches between training and test conditions but no accurate knowledge of the mismatch mechanism is available. A speci c approximate BPC algorithm called Viterbi BPC (VBPC) is proposed for both isolated word and continuous speech recognition. The proposed...

The notion of using computational methods for evaluating cognitive stimulation therapy (CST) based on the synchronized recording of photoplethysmographic (PPG) signals of care-givers and participants offers an objective and cost-effective analysis in health care to improve the patient’s quality of life. While computer models are promising as a useful tool for such a purpose, a question of inter...

This study begins to explore the importance of the physiological domain in voice transformation. A general approach is outlined for transforming the voice quality of sentence-level speech while maintaining the same phonetic content. Transformations will eventually include gender, age, voice quality, emotional state, disordered state, dialect or impersonation. In this paper, only a specific voic...

Formants are regarded as the basic building blocks of vowels; however, they are very rarely used as features for difficult automatic speech recognition tasks. Formant based research is generally focused on formant extraction, because of the assumption that a better formant extraction method is the only manner to increase the effectiveness of formants. We challenge this assumption by investigati...

Spelling recognition has been used for several purposes, such as enhancing speech recognition systems and implementing name retrieval systems. Tone information is an important clue, in addition to phones, for recognizing speeches in tonal languages. In this paper, we present a method to improve accuracy of spelling recognition in Thai, a tonal language, by incorporating tonerelated acoustic fea...

Accurate loss reserves are essential for insurers to maintain adequate capital and to efficiently price their insurance products. Loss reserving for Property & Casualty insurance is usually based on macro-level models with aggregate data in a run-off triangle. The macro-level models may generate material errors in the reserve estimates when assumptions underlying the estimates evolve over time ...