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<Paper uid="W05-0212">
  <Title>A Software Tool for Teaching Reading Based on Text-to-Speech Letter-to-Phoneme Rules</Title>
  <Section position="3" start_page="0" end_page="77" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Learning to read a language like English involves learning many different operations, including phonemic awareness, word recognition, fluency, verbal comprehension, and expression. The research in this project focuses on the pronunciation aspect of reading from the printed page: understanding how letters, or graphemes, in words are related to sounds, or phonemes.</Paragraph>
    <Paragraph position="1"> Most people recognize that the relationship between English orthography and phonetic representation is complex and somewhat arbitrary.</Paragraph>
    <Paragraph position="2"> Although there is significant evidence that phonological information plays an important role in word reading (Kayner, Foorman, Perfetti, Pesetsky, and Seidenberg, 2001), the precise role of &amp;quot;phonics rules&amp;quot; that would allow a learner to &amp;quot;sound out&amp;quot; a printed word has been debated by educators as well as by cognitive psychologists, and many versions of phonics rules have been discussed by educators.</Paragraph>
    <Paragraph position="3"> A classic paper by Clymer (1963) argued that most of the phonics generalizations taught in elementary school are not valid most of the time.</Paragraph>
    <Paragraph position="4"> Clymer found that for many of the rules, there were so many exceptions that the rule had little utility as a generalization for teaching learners to sound out a word of English. However, the Clymer results do not necessarily mean that phonic generalizations are not useful to readers. Since Clymer, there have been many papers that have suggested alternate formulations of the letter-to-phoneme rules for teaching reading. For example, a recent study by Johnston (2001) found one reason that Clymer considered phonics rules to be unreliable is because the rules he evaluated were too general. Today, there is no consensus on a set of rules, nor does there exist any complete, explicit rule system that &amp;quot;decodes&amp;quot; any word or proper name of English for learners.</Paragraph>
    <Paragraph position="5"> E-Speech's letter-to-phoneme (LTP) software, developed over many years for text-to-speech and speech recognition applications, uses proprietary rules to produce pronunciations for any input text.</Paragraph>
    <Paragraph position="6"> We have adapted the LTP software into a prototype web-based, interactive online system that teaches word pronunciation by explicitly presenting rules for those words/names pronounced according to regular rules and by showing exceptions to the rules. The system allows students to view families of words that obey any given rule and to view words with the same letter patterns that obey different rules.</Paragraph>
    <Paragraph position="7"> Our intent is to develop a system that can provide phonics training for beginning readers, either children or adults who are native speakers of En- null glish, as well as for nonnative speakers of English and language-disabled learners. We envision the system either as part of an interactive dictionary or general language-teaching package or stand-alone as an instructional tool for teaching word pronunciation. null A major challenge is to identify rules that are useful for learners and to present them effectively.</Paragraph>
    <Paragraph position="8"> We have begun to test our prototype system with nonnative speakers of English who were studying English as a second or foreign language. Our preliminary results indicate that the software was (1) useful in improving nonnative speakers' pronunciation of English words; (2) effective at teaching both &amp;quot;basic&amp;quot; pronunciation rules, such as those commonly taught in phonics programs, and some novel, proprietary pronunciation rules.</Paragraph>
  </Section>
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