while (stream.incrementToken()) {
                final CharTermAttribute att = stream.getAttribute(CharTermAttribute.class);
                final String term = att.toString();
                final int pos = inputStr.indexOf(term, offset);
                if (pos > 0) {
                    final String tmp = inputStr.substring(offset, pos);
                    kanaBuf.append(transliterator.transliterate(tmp));

     * Sets the maximum size of an alpha-numeric term.
     * @param maxAlphanumTermSize The max size of an alpha-numeric term.
     */
    public void setMaxAlphanumTermSize(final int maxAlphanumTermSize) {
        this.maxAlphanumTermSize = maxAlphanumTermSize;
    }

    /**
     * Sets the maximum size of a symbol term.
     * @param maxSymbolTermSize The max size of a symbol term.
     */

        assertTrue(keywords.contains("query"));
    }

    @Test
    public void testGetTermQueryList() {
        // Test with TermQuery
        Term term = new Term("content", "test");
        TermQuery termQuery = new TermQuery(term);
        String[] fields = { "content" };
        List<TermQuery> queryList = SuggestUtil.getTermQueryList(termQuery, fields);
        assertNotNull(queryList);

        }

        private String convertToJapaneseReading(String term) {
            // Simple simulation of Japanese reading conversion
            if ("東京".equals(term)) {
                return "トウキョウ";
            } else if ("大阪".equals(term)) {
                return "オオサカ";
            } else {
                return term.toUpperCase();
            }
        }
    }

    /**

                    final String term = termTokenList.get(i).getTerm();
                    String reading = readingTokenList.get(i).getTerm();
                    if (Strings.isNullOrEmpty(reading)) {
                        reading = term;
                    }
                    reading = transliterator.transliterate(reading);

                    final int pos = text.indexOf(term, offset);
                    if (pos > 0) {

        int matchCount = 0;
        for (int i = 0; i < tokens.size(); i++) {
            final String term = tokens.get(i).getTerm();
            final String reading = readingTokens.get(i).getTerm();
            switch (term) {
            case "fess":
                matchCount++;
                assertEquals("fess", reading);
                break;
            case "検索":

 *       normalization, contents, and contents reading) for a specific field.</li>
 * </ul>
 *
 * @see SuggestAnalyzer
 * @see FieldAnalyzerMapping
 */
public class AnalyzerSettings {
    /** Analyzer name for reading. */
    public static final String READING_ANALYZER = "reading_analyzer";
    /** Analyzer name for reading term. */

 * <li>{@link #ANALYZER_SETTINGS_READING_ANALYZER} - The reading analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_READING_TERM_ANALYZER} - The reading term analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_NORMALIZE_ANALYZER} - The normalize analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_CONTENTS_ANALYZER} - The contents analyzer settings field.</li>

 * </ul>
 *
 * <p>The {@link TextNormalizeContext} class provides a fluent API to configure the text
 * normalization process, including setting initial buffer capacity, maximum term sizes,
 * duplicate term removal, and custom space characters.
 *
 * <p>Example usage:
 * <pre>{@code
 * Reader reader = new StringReader("Example text to normalize.");
 * String normalizedText = TextUtil.normalizeText(reader)

    }

    private static String parse(String rule, Set<String> dup) {
        String[] values = CSVUtil.parse(rule);
        if (dup.add(values[0]) == false) {
            throw new IllegalArgumentException("Found duplicate term [" + values[0] + "] in user dictionary.");
        }
        return rule;
    }

    public static UserDictionary getUserDictionary(Environment env, Settings settings) {