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https://github.com/Helium314/HeliBoard.git
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move shouldBeAutoCorrected to a separate function
This commit is contained in:
Helium314
parent
0687d10420
commit
f0e5a38fa2
2 changed files with 159 additions and 118 deletions
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@ -33,6 +33,7 @@ import org.dslul.openboard.inputmethod.latin.utils.SuggestionResults;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Locale;
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import javax.annotation.Nonnull;
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@ -139,7 +140,7 @@ public final class Suggest {
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}
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private static SuggestedWordInfo getWhitelistedWordInfoOrNull(
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@Nonnull final ArrayList<SuggestedWordInfo> suggestions) {
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@Nonnull final List<SuggestedWordInfo> suggestions) {
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if (suggestions.isEmpty()) {
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return null;
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}
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@ -160,9 +161,6 @@ public final class Suggest {
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final String typedWordString = wordComposer.getTypedWord();
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final int trailingSingleQuotesCount =
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StringUtils.getTrailingSingleQuotesCount(typedWordString);
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final String consideredWord = trailingSingleQuotesCount > 0
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? typedWordString.substring(0, typedWordString.length() - trailingSingleQuotesCount)
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: typedWordString;
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final SuggestionResults suggestionResults = mDictionaryFacilitator.getSuggestionResults(
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wordComposer.getComposedDataSnapshot(), ngramContext, keyboard,
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@ -191,124 +189,35 @@ public final class Suggest {
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final int firstOccurrenceOfTypedWordInSuggestions =
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SuggestedWordInfo.removeDupsAndTypedWord(typedWordString, suggestionsContainer);
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final SuggestedWordInfo whitelistedWordInfo =
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getWhitelistedWordInfoOrNull(suggestionsContainer);
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final String whitelistedWord = whitelistedWordInfo == null
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? null : whitelistedWordInfo.mWord;
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final boolean resultsArePredictions = !wordComposer.isComposingWord();
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final SuggestedWordInfo firstSuggestionInContainer = suggestionsContainer.isEmpty() ? null : suggestionsContainer.get(0);
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// SuggestedWordInfos for suggestions for empty word (based only on previously typed words)
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// done in a weird way to imitate what kotlin does with lazy
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final ArrayList<SuggestedWordInfo> firstAndTypedWordEmptyInfos = new ArrayList<>(2);
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// We allow auto-correction if whitelisting is not required or the word is whitelisted,
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// or if the word had more than one char and was not suggested.
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final boolean allowsToBeAutoCorrected;
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if ((SHOULD_AUTO_CORRECT_USING_NON_WHITE_LISTED_SUGGESTION || whitelistedWord != null)
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|| (consideredWord.length() > 1 && (sourceDictionaryOfRemovedWord == null)) // more than 1 letter and not in dictionary
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) {
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allowsToBeAutoCorrected = true;
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} else if (firstSuggestionInContainer != null && !typedWordString.isEmpty()) {
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// maybe allow autocorrect, depending on emptyWordSuggestions
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putEmptyWordSuggestions(firstAndTypedWordEmptyInfos,
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ngramContext, keyboard, settingsValuesForSuggestion, inputStyleIfNotPrediction,
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firstSuggestionInContainer.getWord(), typedWordString);
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final SuggestedWordInfo first = firstAndTypedWordEmptyInfos.get(0);
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final SuggestedWordInfo typed = firstAndTypedWordEmptyInfos.get(1);
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if (first == null) {
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allowsToBeAutoCorrected = false; // no autocorrect if first suggestion unknown in this context
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} else if (typed == null) {
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allowsToBeAutoCorrected = true; // autocorrect if typed word not known in this context (this may be too aggressive)
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} else {
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// autocorrect only if suggested word has clearly higher score
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// todo: maybe adjust the score difference? but already 15 requires typing several times (but doesn't go back quickly...)
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// maybe this should depend on mAutoCorrectionThreshold
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// 0.185 for modest, 0.067 for aggressive, negative infinity for very aggressive
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allowsToBeAutoCorrected = (first.mScore - typed.mScore) > 20;
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}
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} else
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allowsToBeAutoCorrected = false;
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// todo: hope autocorrect doesn't trigger too often now (remove this comment if ok)
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// yes, it triggered too often / weirdly in some cases, but hopefully improved
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final boolean hasAutoCorrection;
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// If correction is not enabled, we never auto-correct. This is for example for when
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// the setting "Auto-correction" is "off": we still suggest, but we don't auto-correct.
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if (!isCorrectionEnabled
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// If the word does not allow to be auto-corrected, then we don't auto-correct.
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|| !allowsToBeAutoCorrected
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// If we are doing prediction, then we never auto-correct of course
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|| resultsArePredictions
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// If we don't have suggestion results, we can't evaluate the first suggestion
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// for auto-correction
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|| suggestionResults.isEmpty()
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// If the word has digits, we never auto-correct because it's likely the word
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// was type with a lot of care
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|| wordComposer.hasDigits()
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// If the word is mostly caps, we never auto-correct because this is almost
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// certainly intentional (and careful input)
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|| wordComposer.isMostlyCaps()
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// We never auto-correct when suggestions are resumed because it would be unexpected
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|| wordComposer.isResumed()
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// We don't autocorrect in URL or email input, since websites and emails can be
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// deliberate misspellings of actual words
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|| keyboard.mId.mMode == KeyboardId.MODE_URL
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|| keyboard.mId.mMode == KeyboardId.MODE_EMAIL
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// If we don't have a main dictionary, we never want to auto-correct. The reason
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// for this is, the user may have a contact whose name happens to match a valid
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// word in their language, and it will unexpectedly auto-correct. For example, if
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// the user types in English with no dictionary and has a "Will" in their contact
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// list, "will" would always auto-correct to "Will" which is unwanted. Hence, no
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// main dict => no auto-correct. Also, it would probably get obnoxious quickly.
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// TODO: now that we have personalization, we may want to re-evaluate this decision
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|| !mDictionaryFacilitator.hasAtLeastOneInitializedMainDictionary()
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// If the first suggestion is a shortcut we never auto-correct to it, regardless
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// of how strong it is (whitelist entries are not KIND_SHORTCUT but KIND_WHITELIST).
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// TODO: we may want to have shortcut-only entries auto-correct in the future.
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|| suggestionResults.first().isKindOf(SuggestedWordInfo.KIND_SHORTCUT)) {
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hasAutoCorrection = false;
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} else {
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final SuggestedWordInfo firstSuggestion = suggestionResults.first();
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if (suggestionResults.mFirstSuggestionExceedsConfidenceThreshold
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&& firstOccurrenceOfTypedWordInSuggestions != 0) {
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// todo: mFirstSuggestionExceedsConfidenceThreshold is always false, so currently
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// this branch is useless. remove the related logic, or actually use it
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hasAutoCorrection = true;
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} else if (!AutoCorrectionUtils.suggestionExceedsThreshold(
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firstSuggestion, consideredWord, mAutoCorrectionThreshold)) {
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// todo: maybe also do something here depending on ngram context?
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// Score is too low for autocorrect
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hasAutoCorrection = false;
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} else {
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// We have a high score, so we need to check if this suggestion is in the correct
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// form to allow auto-correcting to it in this language. For details of how this
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// is determined, see #isAllowedByAutoCorrectionWithSpaceFilter.
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// TODO: this should not have its own logic here but be handled by the dictionary.
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final boolean allowed = isAllowedByAutoCorrectionWithSpaceFilter(firstSuggestion);
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// todo: the threshold (currently 1000000) may need tuning
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if (allowed && typedWordFirstOccurrenceWordInfo != null && typedWordFirstOccurrenceWordInfo.mScore > 1000000) {
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// typed word is valid and has good score
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// do not auto-correct if typed word is better prediction than possible correction from ngram context alone
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final SuggestedWordInfo first = firstSuggestionInContainer != null ? firstSuggestionInContainer : firstSuggestion;
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putEmptyWordSuggestions(firstAndTypedWordEmptyInfos,
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ngramContext, keyboard, settingsValuesForSuggestion, inputStyleIfNotPrediction,
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first.getWord(), typedWordString);
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int firstScoreForEmpty = firstAndTypedWordEmptyInfos.get(0) != null ? firstAndTypedWordEmptyInfos.get(0).mScore : 0;
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int typedScoreForEmpty = firstAndTypedWordEmptyInfos.get(1) != null ? firstAndTypedWordEmptyInfos.get(1).mScore : 0;
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final Locale dictLocale = mDictionaryFacilitator.getCurrentLocale();
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// slightly prefer suggestion for the current locale, this is very useful e.g.
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// for Polish i vs English I, or French un vs un->in shortcut in English default dictionary
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if (dictLocale == first.mSourceDict.mLocale)
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firstScoreForEmpty += 1;
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if (dictLocale == typedWordFirstOccurrenceWordInfo.mSourceDict.mLocale)
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typedScoreForEmpty += 1;
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hasAutoCorrection = firstScoreForEmpty >= typedScoreForEmpty;
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} else
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hasAutoCorrection = allowed;
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}
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}
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final boolean[] thoseTwo = shouldBeAutoCorrected(
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trailingSingleQuotesCount,
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typedWordString,
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suggestionsContainer,
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sourceDictionaryOfRemovedWord,
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firstAndTypedWordEmptyInfos,
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() -> {
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final SuggestedWordInfo firstSuggestionInContainer = suggestionsContainer.isEmpty() ? null : suggestionsContainer.get(0);
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SuggestedWordInfo first = firstSuggestionInContainer != null ? firstSuggestionInContainer : suggestionResults.first();
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putEmptyWordSuggestions(firstAndTypedWordEmptyInfos, ngramContext, keyboard,
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settingsValuesForSuggestion, inputStyleIfNotPrediction, first.getWord(), typedWordString);
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},
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isCorrectionEnabled,
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keyboard.mId.mMode,
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wordComposer,
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suggestionResults,
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mDictionaryFacilitator,
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mAutoCorrectionThreshold,
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firstOccurrenceOfTypedWordInSuggestions,
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typedWordFirstOccurrenceWordInfo
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);
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final boolean allowsToBeAutoCorrected = thoseTwo[0];
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final boolean hasAutoCorrection = thoseTwo[1];
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final SuggestedWordInfo typedWordInfo = new SuggestedWordInfo(typedWordString,
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"" /* prevWordsContext */, SuggestedWordInfo.MAX_SCORE,
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@ -380,6 +289,138 @@ public final class Suggest {
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return infos;
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}
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// returns [allowsToBeAutoCorrected, hasAutoCorrection]
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static boolean[] shouldBeAutoCorrected(
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final int trailingSingleQuotesCount,
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final String typedWordString,
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final List<SuggestedWordInfo> suggestionsContainer,
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final Dictionary sourceDictionaryOfRemovedWord,
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final List<SuggestedWordInfo> firstAndTypedWordEmptyInfos,
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final Runnable putEmptyWordSuggestions,
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final boolean isCorrectionEnabled,
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final int keyboardIdMode,
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final WordComposer wordComposer,
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final SuggestionResults suggestionResults,
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final DictionaryFacilitator dictionaryFacilitator,
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final float autoCorrectionThreshold,
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final int firstOccurrenceOfTypedWordInSuggestions,
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final SuggestedWordInfo typedWordFirstOccurrenceWordInfo
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) {
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final String consideredWord = trailingSingleQuotesCount > 0
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? typedWordString.substring(0, typedWordString.length() - trailingSingleQuotesCount)
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: typedWordString;
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final SuggestedWordInfo whitelistedWordInfo =
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getWhitelistedWordInfoOrNull(suggestionsContainer);
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final String whitelistedWord = whitelistedWordInfo == null
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? null : whitelistedWordInfo.mWord;
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final SuggestedWordInfo firstSuggestionInContainer = suggestionsContainer.isEmpty() ? null : suggestionsContainer.get(0);
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// We allow auto-correction if whitelisting is not required or the word is whitelisted,
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// or if the word had more than one char and was not suggested.
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final boolean allowsToBeAutoCorrected;
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if ((SHOULD_AUTO_CORRECT_USING_NON_WHITE_LISTED_SUGGESTION || whitelistedWord != null)
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|| (consideredWord.length() > 1 && (sourceDictionaryOfRemovedWord == null)) // more than 1 letter and not in dictionary
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) {
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allowsToBeAutoCorrected = true;
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} else if (firstSuggestionInContainer != null && !typedWordString.isEmpty()) {
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// maybe allow autocorrect, depending on emptyWordSuggestions
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putEmptyWordSuggestions.run();
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final SuggestedWordInfo first = firstAndTypedWordEmptyInfos.get(0);
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final SuggestedWordInfo typed = firstAndTypedWordEmptyInfos.get(1);
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if (first == null) {
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allowsToBeAutoCorrected = false; // no autocorrect if first suggestion unknown in this context
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} else if (typed == null) {
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allowsToBeAutoCorrected = true; // autocorrect if typed word not known in this context (this may be too aggressive)
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} else {
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// autocorrect only if suggested word has clearly higher score
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// todo: maybe adjust the score difference? but already 15 requires typing several times (but doesn't go back quickly...)
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// maybe this should depend on mAutoCorrectionThreshold
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// 0.185 for modest, 0.067 for aggressive, negative infinity for very aggressive
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allowsToBeAutoCorrected = (first.mScore - typed.mScore) > 20;
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}
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} else
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allowsToBeAutoCorrected = false;
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// todo: hope autocorrect doesn't trigger too often now (remove this comment if ok)
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// yes, it triggered too often / weirdly in some cases, but hopefully improved
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final boolean hasAutoCorrection;
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// If correction is not enabled, we never auto-correct. This is for example for when
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// the setting "Auto-correction" is "off": we still suggest, but we don't auto-correct.
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if (!isCorrectionEnabled
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// If the word does not allow to be auto-corrected, then we don't auto-correct.
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|| !allowsToBeAutoCorrected
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// If we are doing prediction, then we never auto-correct of course
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|| !wordComposer.isComposingWord()
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// If we don't have suggestion results, we can't evaluate the first suggestion
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// for auto-correction
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|| suggestionResults.isEmpty()
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// If the word has digits, we never auto-correct because it's likely the word
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// was type with a lot of care
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|| wordComposer.hasDigits()
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// If the word is mostly caps, we never auto-correct because this is almost
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// certainly intentional (and careful input)
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|| wordComposer.isMostlyCaps()
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// We never auto-correct when suggestions are resumed because it would be unexpected
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|| wordComposer.isResumed()
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// We don't autocorrect in URL or email input, since websites and emails can be
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// deliberate misspellings of actual words
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|| keyboardIdMode == KeyboardId.MODE_URL
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|| keyboardIdMode == KeyboardId.MODE_EMAIL
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// If we don't have a main dictionary, we never want to auto-correct. The reason
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// for this is, the user may have a contact whose name happens to match a valid
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// word in their language, and it will unexpectedly auto-correct. For example, if
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// the user types in English with no dictionary and has a "Will" in their contact
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// list, "will" would always auto-correct to "Will" which is unwanted. Hence, no
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// main dict => no auto-correct. Also, it would probably get obnoxious quickly.
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// TODO: now that we have personalization, we may want to re-evaluate this decision
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|| !dictionaryFacilitator.hasAtLeastOneInitializedMainDictionary()
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// If the first suggestion is a shortcut we never auto-correct to it, regardless
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// of how strong it is (whitelist entries are not KIND_SHORTCUT but KIND_WHITELIST).
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// TODO: we may want to have shortcut-only entries auto-correct in the future.
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|| suggestionResults.first().isKindOf(SuggestedWordInfo.KIND_SHORTCUT)) {
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hasAutoCorrection = false;
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} else {
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final SuggestedWordInfo firstSuggestion = suggestionResults.first();
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if (suggestionResults.mFirstSuggestionExceedsConfidenceThreshold
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&& firstOccurrenceOfTypedWordInSuggestions != 0) {
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// todo: mFirstSuggestionExceedsConfidenceThreshold is always false, so currently
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// this branch is useless. remove the related logic, or actually use it
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hasAutoCorrection = true;
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} else if (!AutoCorrectionUtils.suggestionExceedsThreshold(
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firstSuggestion, consideredWord, autoCorrectionThreshold)) {
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// todo: maybe also do something here depending on ngram context?
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// Score is too low for autocorrect
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hasAutoCorrection = false;
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} else {
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// We have a high score, so we need to check if this suggestion is in the correct
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// form to allow auto-correcting to it in this language. For details of how this
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// is determined, see #isAllowedByAutoCorrectionWithSpaceFilter.
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// TODO: this should not have its own logic here but be handled by the dictionary.
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final boolean allowed = isAllowedByAutoCorrectionWithSpaceFilter(firstSuggestion);
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// todo: the threshold (currently 1000000) may need tuning
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if (allowed && typedWordFirstOccurrenceWordInfo != null && typedWordFirstOccurrenceWordInfo.mScore > 1000000) {
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// typed word is valid and has good score
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// do not auto-correct if typed word is better prediction than possible correction from ngram context alone
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final SuggestedWordInfo first = firstSuggestionInContainer != null ? firstSuggestionInContainer : firstSuggestion;
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putEmptyWordSuggestions.run();
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int firstScoreForEmpty = firstAndTypedWordEmptyInfos.get(0) != null ? firstAndTypedWordEmptyInfos.get(0).mScore : 0;
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int typedScoreForEmpty = firstAndTypedWordEmptyInfos.get(1) != null ? firstAndTypedWordEmptyInfos.get(1).mScore : 0;
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final Locale dictLocale = dictionaryFacilitator.getCurrentLocale();
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// slightly prefer suggestion for the current locale, this is very useful e.g.
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// for Polish i vs English I, or French un vs un->in shortcut in English default dictionary
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if (dictLocale == first.mSourceDict.mLocale)
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firstScoreForEmpty += 1;
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if (dictLocale == typedWordFirstOccurrenceWordInfo.mSourceDict.mLocale)
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typedScoreForEmpty += 1;
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hasAutoCorrection = firstScoreForEmpty >= typedScoreForEmpty;
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} else
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hasAutoCorrection = allowed;
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}
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}
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return new boolean[]{ allowsToBeAutoCorrected, hasAutoCorrection };
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}
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// Retrieves suggestions for the batch input
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// and calls the callback function with the suggestions.
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private void getSuggestedWordsForBatchInput(final WordComposer wordComposer,
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@ -383,7 +383,7 @@ public class SuggestedWords {
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/**
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* This will always remove the higher index if a duplicate is found.
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* Will also remove al occurrences of the typed word.
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* Will also remove all occurrences of the typed word.
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*
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* @return position of typed word in the candidate list
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*/
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@ -394,7 +394,7 @@ public class SuggestedWords {
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return -1;
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}
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int firstOccurrenceOfWord = -1;
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if (!TextUtils.isEmpty(typedWord)) {
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if (typedWord != null && typedWord.length() > 0) {
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firstOccurrenceOfWord = removeSuggestedWordInfoFromList(
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typedWord, candidates, -1 /* startIndexExclusive */);
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}
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