A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

Enhancing Skills Transfer through Problem-based Learning. Department of Computer Science, Technical Report Series. NUIM-CS-TR-2005-13

Problem-based Learning (PBL) has proved itself as a successful teaching and learning environment in the medical field, and has slowly become the preferred teaching and learning method in other disciplines. In this report we look at the learning theories that have influenced PBL and investigate the use of PBL in computer science. We extend the boundaries of PBL and software engineering education with a proposal that fully integrates PBL into a computer science and software engineering degree structure. The objective of this proposal is to produce graduates who can successfully transfer their knowledge and skills into practical situations in new domains

Enhancing Skills Transfer through Problem-based Learning. Department of Computer Science, Technical Report Series. NUIM-CS-TR-2005-13

Problem-based Learning (PBL) has proved itself as a successful teaching and learning environment in the medical field, and has slowly become the preferred teaching and learning method in other disciplines. In this report we look at the learning theories that have influenced PBL and investigate the use of PBL in computer science. We extend the boundaries of PBL and software engineering education with a proposal that fully integrates PBL into a computer science and software engineering degree structure. The objective of this proposal is to produce graduates who can successfully transfer their knowledge and skills into practical situations in new domains

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

A Speech Feature Vector based on its Maximum Phase Component

This paper examines the performance of a vowel classification scheme using a new form of feature vector derived from a decomposition of the speech segment into Maximum Phase and Minimum Phase components. Justification for this approach in terms of its perceptual relevance is first made, followed by a signal processing scheme to obtain the components. The form for the feature vector is then discussed. Lastly, experimental work compares the performance of this new feature vector under a variety of distortion conditions with the contemporary popular choice of Mel-Frequency Cepstral Coefficients

Enhancing Skills Transfer through Problem-based Learning. Department of Computer Science, Technical Report Series. NUIM-CS-TR-2005-13

Problem-based Learning (PBL) has proved itself as a successful teaching and learning environment in the medical field, and has slowly become the preferred teaching and learning method in other disciplines. In this report we look at the learning theories that have influenced PBL and investigate the use of PBL in computer science. We extend the boundaries of PBL and software engineering education with a proposal that fully integrates PBL into a computer science and software engineering degree structure. The objective of this proposal is to produce graduates who can successfully transfer their knowledge and skills into practical situations in new domains