Text input device comprising: a text prediction component for predicting a plurality of follow-up words based on a text context, the text prediction component outputting a set of candidate words ; a character handwriting recognition component for recognizing handwritten character candidates, wherein a character is one out of a letter, a digit and a punctuation; a candidate word filtering component for filtering the set of candidate words received from the text prediction component based on the output of the character handwriting recognition component ; a word presentation component for presenting the filtered set of candidate words to a user of the device ; and a word selection component for receiving a user selection of a presented candidate word from the user; wherein the character handwriting recognition component is configured for: determining, via a trained neural network, a plurality of character candidates for a particular handwriting input of one character, the plurality of character candidates being determined based upon handwriting input received from a touch sensitive input field ; and outputting the top N character candidates out of the plurality of character candidates as determined by the neural network, with N being equal to or greater than 2, wherein an output vector of the neural network comprises for at least one given character more than one position, each position corresponding to a different visual form of the character. a text prediction component for predicting a plurality of follow-up words based on a text context, the text prediction component outputting a set of candidate words ; a character handwriting recognition component for recognizing handwritten character candidates, wherein a character is one out of a letter, a digit and a punctuation; a candidate word filtering component for filtering the set of candidate words received from the text prediction component based on the output of the character handwriting recognition component ; a word presentation component for presenting the filtered set of candidate words to a user of the device ; and a word selection component for receiving a user selection of a presented candidate word from the user; wherein the character handwriting recognition component is configured for: determining, via a trained neural network, a plurality of character candidates for a particular handwriting input of one character, the plurality of character candidates being determined based upon handwriting input received from a touch sensitive input field ; and outputting the top N character candidates out of the plurality of character candidates as determined by the neural network, with N being equal to or greater than 2, wherein an output vector of the neural network comprises for at least one given character more than one position, each position corresponding to a different visual form of the character. determining, via a trained neural network, a plurality of character candidates for a particular handwriting input of one character, the plurality of character candidates being determined based upon handwriting input received from a touch sensitive input field ; and outputting the top N character candidates out of the plurality of character candidates as determined by the neural network, with N being equal to or greater than 2, wherein an output vector of the neural network comprises for at least one given character more than one position, each position corresponding to a different visual form of the character. <EOS>