Abstract In this paper, we highlight the role of typology in providing an empirical basis for explanation within Evolutionary Phonology with a focus on rare sound patterns and extra-phonetic explanation. Broad typological surveys or macro-typologies that include phonetic detail may, at once, support universal tendencies document patterns, offering arguments theories which based are emergent pro...

Significance Infants become attuned to the sounds of their native language(s) before they even speak. Hypotheses about what is being learned by infants have traditionally driven researchers’ attempts understand this surprising phenomenon. Here, we propose start, instead, from hypotheses how might learn. To implement mechanism-driven approach, introduce a quantitative modeling framework based on...

In the past, phonetic transcriptions were made using a wide variety of fonts and formats, which hampered the development of phonetic text processing tools. Today, however, the increasing number of language documentation projects making their data freely available over the Web, combined with the adoption of the Unicode Standard by linguists as "best practice" character encoding, present linguist...

In this paper, we use mutual information to characterize the distributions of phonetic and speaker/channel information in a timefrequency space. The mutual information (MI) between the phonetic label and one feature, and the joint mutual information (JMI) between the phonetic label and two or three features are estimated . The Miller's bias formulas for entropy and mutual information estimates ...

Title of dissertation: SPEECH RECOGNITION BASED ON PHONETIC FEATURES AND ACOUSTIC LANDMARKS Amit Juneja, Doctor of Philosophy, 2004 Dissertation directed by: Carol Espy-Wilson Department of Electrical and Computer Engineering A probabilistic and statistical framework is presented for automatic speech recognition based on a phonetic feature representation of speech sounds. In this acoustic-phone...

Extending the phone set is one common approach for dealing with phonetic confusions in spontaneous speech. We propose using likelihood ratio test as a confidence measure for automatic phone set extension to model phonetic confusions. We first extend the standard phone set using dynamic programming (DP) alignment to cover all possible phonetic confusions in training data. Likelihood ratio test i...

This paper reports on the correlation between word confusion matrices from Word-Error-Rate (WER) experiments and different phonetic distance measures. The investigated phonetic distance measures are based on the minimum-edit-distances between phonetic transcriptions and the distances between Hidden-Markov-Models (HMM). We show that phonetic distance measures are correlated with word confusion. ...

Given a baseline speech coder and speech with an available phonetic class segmentation, a number of potential enhancements to that coder become possible. While the quality of speech segmentation by phoneme and phonetic class is constantly improving, we use TIMIT to generate phonetic class segmentation as a basis for initial testing of these techniques. Using coders drawn from the MELP family, w...

Learning phonetic categories is one of the first steps to learning a language, yet is hard to do using only distributional phonetic information. Semantics could potentially be useful, since words with different meanings have distinct phonetics, but it is unclear how many word meanings are known to infants learning phonetic categories. We show that attending to a weaker source of semantics, in t...