To build a robust pitch accent prediction system, we need to understand the effects of speech genre and speaker variation. This paper reports our studies on genre and speaker variation in pitch accent placement and their effects on automatic pitch accent prediction. We find some interesting accentuation pattern differences that can be attributed to speech genre, and a set of textual features th...

Content management is focused on managing a variety of content such as Web sites, documents, and content integrated from multiple sources. Genres communicative types with similar substance and form can be thought of as prototypical, user-defined models of the content used in recurrent work tasks. This paper discusses a study in which the theory and research findings related to genres were opera...

Genre identification is a critical facet of text comprehension, but very little is known about the process and information constraints of classifying texts by genres. In this study, higherskill and lower-skill participants read 210 sentences from three genres. The words in the sentences were presented sequentially, one at a time. With each new word, participants decided whether the sentences ca...

We consider methods for training a prosodic classifier using labeled training data from a different genre than the one on which the system will be deployed. Two binary tasks are considered: word-level pitch accent and phrase boundary detection. Using radio news and conversational telephone speech, we consider cross-genre training using acoustic and textual features, and find that acoustic featu...

This dissertation presents, discusses, and sheds some light on the problems that appear when computers try to automatically classify musical genres from audio signals. In particular, a method is proposed for the automatic music genre classification by using a computational approach that is inspired in music cognition and musicology in addition to Music Information Retrieval techniques. In this ...

We adapt the hierarchical attention network for the task of genre classification using lyrics. Utilising a large dataset of intact song lyrics we apply a recurrent neural network model which tries to learn importance of words, lines and sections in the genre classification task. This hierarchical structure attempts to replicate the structure of lyrics and enable learning of which sections, line...

Classification of musical genres gives a useful measure of similarity and is often the most useful descriptor of a musical piece. Previous techniques to use hidden Markov models (HMMs) for automatic genre classification have used a single HMM to model an entire song or genre. This paper provides a framework to give finer segmentation of HMMs through acoustic segment modeling. Modeling each of t...

In this paper, we present an inferential model for text type and genre identification of web pages, where text types are inferred using a modified form of Bayes’ theorem, and genres are derived using a few simple if-then rules. As the genre system on the web is a complex reality, and web pages are much more unpredictable and individualized than paper documents, we propose this approach as an al...

This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected based on the literature and the observation of the corpus. Thirdly, these features were extracted from the corpus to obtain a data set. Finally, three machine learning algorithms, one for induction of decision trees (J48...