Covington et al., 2005). However, calculating speech rate by hand is a tedious task, which is therefore often not carried out. In this article, we present a script written in the software program Praat (Boersma & Weenink, 2007) that automatically detects syllable nuclei in order to calculate speech rate. The nucleus of a syllable, also called the peak, is the central part of a syllable (most commonly, the vowel in the syllable). Locating these syllable nuclei allows for a computation of number of syllables, which can be used to calculate speech rate.According to Tavakoli and Skehan (2005), fluency is multifaceted in nature. They distinguish three different facets of fluency: breakdown fluency (number and length of pauses), speed and density per time unit (speech rate), and repair fluency (false starts and repetitions). In second language testing practice, fluency is usually a score awarded by human judges who use several aspects of fluency in their judgment. However, Cucchiarini, Strik, and Boves (2002) have shown that of several objectively measured aspects of fluency, speech rate (as measured by phonemes per time unit) is the best predictor of subjective fluency. Kormos and Dénes (2004) likewise have shown that speech rate (in terms of number of syllables per time unit) is a good predictor of subjective fluency. We conclude that, for researchers wanting to include a measure of fluency, speech rate is an important factor to take into account. However, because of time constraints, this measure is often impossible to carry out. For instance, the script presented in this article was written in order to be able to measure the speech rate of 250 participants in a corpus of over 45 h of speech, a task that would take at least 8 months of full-time work for one person to measure by hand. In the context of a large-scale research project on the correlates of speaking proficiency carried out at the University of Amsterdam (What Is Speaking Proficiency: www.hum.uva.nl/wisp), we developed two tools to measure fluency automatically. For the purpose of measuring pauses in running speech, we wrote a script in the software program Praat to automatically detect silence in speech [a simplified version of which is now incorporated in the button To TextGrid (silences) in the Praat software]. For the purpose of estimating the speech rate of speech performances, we wrote a script in Praat that automatically detects syllable nuclei to compute speech rate in terms of syllables per time unit. In this article, we will present and validate the script for detecting syllable nuclei.For automatic speech recognition, speech rate is an important factor as well. Human listeners are able to understand both fast and slow speech. Speech recognizers implemented in computers, however, perform relatively poorly when In this article, we describe a method for automatically detecting syllable nuclei in order to measure speech rate without the need for a transcription. A script written in the software program Praat (Boersma & Weenink, 2007) detects syl...

TE and NL speakers differ less in the way the voiced-voiceless distinction is conveyed than expected. Further research is needed to show whether the main acoustic cue is also perceptually most relevant.

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The role of principal component analysis in vowel acquisition researchZajdo, K.; van der Stelt, J.M.; Wempe, A.G. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Major investments are currently being made in school infrastructure. In Los Angeles alone, 90 new schools are to be constructed in the next 10 to 15 years, and hundreds of existing schools will undergo major renovation. Similar efforts are underway in large urban school districts throughout the country. This presents a unique opportunity to improve acoustical quality in classrooms for future generations of teachers and students. While some school districts are embracing this opportunity, there are substantial challenges to be faced before improvements in classroom acoustical quality are widely realized. Despite recent adoption of the ANSI standard, there are inconsistent views among school administrators and designers on the extent of the problem and the urgency to act. Additionally, there is insufficient data on the incremental costs of achieving improved acoustical quality in new construction or modernization projects. Meanwhile critical design and purchasing decisions are underway. There are promising examples of how school districts can successfully meet these challenges and forge improved acoustical quality in the learning environment. The focus of this discussion is on the use of policy reforms to drive better design and purchasing decisions, and how these decisions can be further influenced by community involvement and interagency collaboration. Issues in meeting the ANSI 12.60 classroom acoustics standard fall into two categories: overcoming design team unwillingness to implement recommended criteria and finding practical methods of meeting issues of reverberation control and HVAC noise control. Solutions to HVAC noise control are emerging; an example is the use of fan coil units in new construction. Education of owners and designers is an ongoing process. It is hoped this paper contributes to a dialogue between the parties involved in school construction. 8:254aAA3. Source attenuating HVAC equipment-Just the facts. Arthur Hallstrom ͑Trane, American Standard, 1515 Mercer Rd., Lexington, KY 40511͒ Current classroom designs range from NC 63 to NC 25. The ASA/ANSI 12.60 Classroom Standard sets a re...