1 /*
2  * Copyright (C) 2014 The Android Open Source Project
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  *      http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 package com.android.inputmethod.latin.utils;
18 
19 import android.util.Log;
20 
21 import com.android.inputmethod.latin.Dictionary;
22 import com.android.inputmethod.latin.DictionaryFacilitator;
23 import com.android.inputmethod.latin.PrevWordsInfo;
24 import com.android.inputmethod.latin.settings.SpacingAndPunctuations;
25 
26 import java.util.ArrayList;
27 import java.util.List;
28 import java.util.Locale;
29 
30 // Note: this class is used as a parameter type of a native method. You should be careful when you
31 // rename this class or field name. See BinaryDictionary#addMultipleDictionaryEntriesNative().
32 public final class LanguageModelParam {
33     private static final String TAG = LanguageModelParam.class.getSimpleName();
34     private static final boolean DEBUG = false;
35     private static final boolean DEBUG_TOKEN = false;
36 
37     // For now, these probability values are being referred to only when we add new entries to
38     // decaying dynamic binary dictionaries. When these are referred to, what matters is 0 or
39     // non-0. Thus, it's not meaningful to compare 10, 100, and so on.
40     // TODO: Revise the logic in ForgettingCurveUtils in native code.
41     private static final int UNIGRAM_PROBABILITY_FOR_VALID_WORD = 100;
42     private static final int UNIGRAM_PROBABILITY_FOR_OOV_WORD = Dictionary.NOT_A_PROBABILITY;
43     private static final int BIGRAM_PROBABILITY_FOR_VALID_WORD = 10;
44     private static final int BIGRAM_PROBABILITY_FOR_OOV_WORD = Dictionary.NOT_A_PROBABILITY;
45 
46     public final CharSequence mTargetWord;
47     public final int[] mWord0;
48     public final int[] mWord1;
49     // TODO: this needs to be a list of shortcuts
50     public final int[] mShortcutTarget;
51     public final int mUnigramProbability;
52     public final int mBigramProbability;
53     public final int mShortcutProbability;
54     public final boolean mIsNotAWord;
55     public final boolean mIsBlacklisted;
56     // Time stamp in seconds.
57     public final int mTimestamp;
58 
59     // Constructor for unigram. TODO: support shortcuts
LanguageModelParam(final CharSequence word, final int unigramProbability, final int timestamp)60     public LanguageModelParam(final CharSequence word, final int unigramProbability,
61             final int timestamp) {
62         this(null /* word0 */, word, unigramProbability, Dictionary.NOT_A_PROBABILITY, timestamp);
63     }
64 
65     // Constructor for unigram and bigram.
LanguageModelParam(final CharSequence word0, final CharSequence word1, final int unigramProbability, final int bigramProbability, final int timestamp)66     public LanguageModelParam(final CharSequence word0, final CharSequence word1,
67             final int unigramProbability, final int bigramProbability,
68             final int timestamp) {
69         mTargetWord = word1;
70         mWord0 = (word0 == null) ? null : StringUtils.toCodePointArray(word0);
71         mWord1 = StringUtils.toCodePointArray(word1);
72         mShortcutTarget = null;
73         mUnigramProbability = unigramProbability;
74         mBigramProbability = bigramProbability;
75         mShortcutProbability = Dictionary.NOT_A_PROBABILITY;
76         mIsNotAWord = false;
77         mIsBlacklisted = false;
78         mTimestamp = timestamp;
79     }
80 
81     // Process a list of words and return a list of {@link LanguageModelParam} objects.
createLanguageModelParamsFrom( final List<String> tokens, final int timestamp, final DictionaryFacilitator dictionaryFacilitator, final SpacingAndPunctuations spacingAndPunctuations, final DistracterFilter distracterFilter)82     public static ArrayList<LanguageModelParam> createLanguageModelParamsFrom(
83             final List<String> tokens, final int timestamp,
84             final DictionaryFacilitator dictionaryFacilitator,
85             final SpacingAndPunctuations spacingAndPunctuations,
86             final DistracterFilter distracterFilter) {
87         final ArrayList<LanguageModelParam> languageModelParams = new ArrayList<>();
88         final int N = tokens.size();
89         PrevWordsInfo prevWordsInfo = PrevWordsInfo.EMPTY_PREV_WORDS_INFO;
90         for (int i = 0; i < N; ++i) {
91             final String tempWord = tokens.get(i);
92             if (StringUtils.isEmptyStringOrWhiteSpaces(tempWord)) {
93                 // just skip this token
94                 if (DEBUG_TOKEN) {
95                     Log.d(TAG, "--- isEmptyStringOrWhiteSpaces: \"" + tempWord + "\"");
96                 }
97                 continue;
98             }
99             if (!DictionaryInfoUtils.looksValidForDictionaryInsertion(
100                     tempWord, spacingAndPunctuations)) {
101                 if (DEBUG_TOKEN) {
102                     Log.d(TAG, "--- not looksValidForDictionaryInsertion: \""
103                             + tempWord + "\"");
104                 }
105                 // Sentence terminator found. Split.
106                 prevWordsInfo = PrevWordsInfo.EMPTY_PREV_WORDS_INFO;
107                 continue;
108             }
109             if (DEBUG_TOKEN) {
110                 Log.d(TAG, "--- word: \"" + tempWord + "\"");
111             }
112             final LanguageModelParam languageModelParam =
113                     detectWhetherVaildWordOrNotAndGetLanguageModelParam(
114                             prevWordsInfo, tempWord, timestamp, dictionaryFacilitator,
115                             distracterFilter);
116             if (languageModelParam == null) {
117                 continue;
118             }
119             languageModelParams.add(languageModelParam);
120             prevWordsInfo = prevWordsInfo.getNextPrevWordsInfo(
121                     new PrevWordsInfo.WordInfo(tempWord));
122         }
123         return languageModelParams;
124     }
125 
detectWhetherVaildWordOrNotAndGetLanguageModelParam( final PrevWordsInfo prevWordsInfo, final String targetWord, final int timestamp, final DictionaryFacilitator dictionaryFacilitator, final DistracterFilter distracterFilter)126     private static LanguageModelParam detectWhetherVaildWordOrNotAndGetLanguageModelParam(
127             final PrevWordsInfo prevWordsInfo, final String targetWord, final int timestamp,
128             final DictionaryFacilitator dictionaryFacilitator,
129             final DistracterFilter distracterFilter) {
130         final Locale locale = dictionaryFacilitator.getLocale();
131         if (locale == null) {
132             return null;
133         }
134         if (dictionaryFacilitator.isValidWord(targetWord, false /* ignoreCase */)) {
135             return createAndGetLanguageModelParamOfWord(prevWordsInfo, targetWord, timestamp,
136                     true /* isValidWord */, locale, distracterFilter);
137         }
138 
139         final String lowerCaseTargetWord = targetWord.toLowerCase(locale);
140         if (dictionaryFacilitator.isValidWord(lowerCaseTargetWord, false /* ignoreCase */)) {
141             // Add the lower-cased word.
142             return createAndGetLanguageModelParamOfWord(prevWordsInfo, lowerCaseTargetWord,
143                     timestamp, true /* isValidWord */, locale, distracterFilter);
144         }
145 
146         // Treat the word as an OOV word.
147         return createAndGetLanguageModelParamOfWord(prevWordsInfo, targetWord, timestamp,
148                 false /* isValidWord */, locale, distracterFilter);
149     }
150 
createAndGetLanguageModelParamOfWord( final PrevWordsInfo prevWordsInfo, final String targetWord, final int timestamp, final boolean isValidWord, final Locale locale, final DistracterFilter distracterFilter)151     private static LanguageModelParam createAndGetLanguageModelParamOfWord(
152             final PrevWordsInfo prevWordsInfo, final String targetWord, final int timestamp,
153             final boolean isValidWord, final Locale locale,
154             final DistracterFilter distracterFilter) {
155         final String word;
156         if (StringUtils.getCapitalizationType(targetWord) == StringUtils.CAPITALIZE_FIRST
157                 && !prevWordsInfo.isValid() && !isValidWord) {
158             word = targetWord.toLowerCase(locale);
159         } else {
160             word = targetWord;
161         }
162         // Check whether the word is a distracter to words in the dictionaries.
163         if (distracterFilter.isDistracterToWordsInDictionaries(prevWordsInfo, word, locale)) {
164             if (DEBUG) {
165                 Log.d(TAG, "The word (" + word + ") is a distracter. Skip this word.");
166             }
167             return null;
168         }
169         final int unigramProbability = isValidWord ?
170                 UNIGRAM_PROBABILITY_FOR_VALID_WORD : UNIGRAM_PROBABILITY_FOR_OOV_WORD;
171         if (!prevWordsInfo.isValid()) {
172             if (DEBUG) {
173                 Log.d(TAG, "--- add unigram: current("
174                         + (isValidWord ? "Valid" : "OOV") + ") = " + word);
175             }
176             return new LanguageModelParam(word, unigramProbability, timestamp);
177         }
178         if (DEBUG) {
179             Log.d(TAG, "--- add bigram: prev = " + prevWordsInfo + ", current("
180                     + (isValidWord ? "Valid" : "OOV") + ") = " + word);
181         }
182         final int bigramProbability = isValidWord ?
183                 BIGRAM_PROBABILITY_FOR_VALID_WORD : BIGRAM_PROBABILITY_FOR_OOV_WORD;
184         return new LanguageModelParam(prevWordsInfo.mPrevWordsInfo[0].mWord, word,
185                 unigramProbability, bigramProbability, timestamp);
186     }
187 }
188