T9 - Keyboard Emulator

const starterDictionary = '2': ['a', 'b', 'c'], '22': ['aa', 'ab', 'ac', 'ba', 'bb', 'bc', 'ca', 'cb', 'cc'], '23': ['ad', 'ae', 'af', 'bd', 'be', 'bf', 'cd', 'ce', 'cf'], '4663': ['good', 'home', 'gone', 'hood'], '43556': ['hello'], '96753': ['world', 'words'], '843': ['the', 'tie', 'vid'], '2865': ['bunk', 'cunt', 'auto'], '5464': ['king', 'link', 'jink'], '7364': ['send', 'rend', 'pend'] ; 1. Next Word Prediction Allow cycling through predictions with a "Next" key (usually * ) 2. Add Word to Dictionary Let users add new words that aren't recognized 3. Frequency-Based Sorting Sort predictions by how often the user selects them

wordToSequence(word) return word.toLowerCase().split('').map(ch => for (let [key, letters] of Object.entries(this.keyMap)) if (letters.includes(ch)) return key; return ch === ' ' ? '0' : ''; ).join(''); t9 keyboard emulator

Store common words mapped to their T9 sequences: const starterDictionary = '2': ['a', 'b', 'c'], '22':

# Example word dictionary t9_dict = '4663': ['good', 'home', 'gone'], '2273': ['case', 'care', 'base'], '96753': ['words', 'world'], '43556': ['hello'], '843': ['the', 'tie', 'vid'] Frequency-Based Sorting Sort predictions by how often the

class SmartT9: def __init__(self): self.word_frequency = {} def get_predictions(self, sequence): words = self.dictionary.get(sequence, []) return sorted(words, key=lambda w: self.word_frequency.get(w, 0), reverse=True)