Data processing: presentation processing of document – operator i – Presentation processing of document – Layout
Reexamination Certificate
1999-10-05
2004-09-07
Shah, Sanjiv (Department: 2176)
Data processing: presentation processing of document, operator i
Presentation processing of document
Layout
C715S252000, C704S004000, C704S009000
Reexamination Certificate
active
06789231
ABSTRACT:
FIELD OF THE INVENTION
The invention relates generally to methods for entering text into a computer and, more particularly, relates to providing alternatives for a text selection derived from multiple stochastic input sources.
BACKGROUND OF THE INVENTION
Computer users have traditionally entered text into word processors through a keyboard and mouse. In recent years, however, word processors have become more sophisticated by allowing users to enter text into them through other input methods, such as speech or handwriting. Although a computer cannot always interpret such input with complete accuracy, a computer can generate a list of text alternatives for the input. Furthermore, the computer can often assign to each alternative a probability that the alternative is the one the user intended. Input that produces such probabilistic results is called “stochastic input,” while input that can be accurately determined, such as typed text, is called “non-stochastic input.”
Typically, text produced in a word processor from stochastic input must be heavily edited by the user in order to produce the text intended by the user when he or she created the stochastic input. The editing process has been simplified by allowing the user to select text created from stochastic data and request alternatives for the text selection. In response, the computer can provide the user with alternatives for the text selection through a graphical user interface. If the user chooses one of the alternatives, the computer replaces the text selection with the selected alternative.
Suppose that after a user creates text in a word processor by providing the word processor with stochastic input, such as speech, the user then edits the text. The user may, for example, replace a word of the text with a new word typed into the computer with a keyboard. Current word processors do not incorporate typed text edits into the alternatives they provide for an edited text selection. Thus, there is a need in the art for a method of providing alternatives to edited text derived from stochastic input.
Another problem occurs if the user attempts to request alternatives for a text selection spanning multiple stochastic input sources. For instance, the user may request alternatives for a text selection containing a word based on handwriting input and a word based on speech input. Current word processors are not capable of providing meaningful alternatives for such a text selection. Thus, there is also a need in the art for a method of providing alternatives for a text selection derived from multiple stochastic input sources.
An input method editor (IME) is another word processor input method that produces stochastic data. Generally, an IME converts input into foreign language text. The input into an IME may, for example, be typed text entered into the computer through a keyboard and mouse. An IME is especially useful for creating ideograms in Asian and other languages. Because there are many more ideograms in such languages than there are keys on a keyboard, entering a particular ideogram into the computer typically requires multiples keystrokes, which the IME interprets as a composed character.
In a typical IME, a user may type in English characters defining a phonetic spelling for a desired Chinese character. Since many Chinese characters have similar pronunciations, the typed phonetic spelling may represent any one of a number of different Chinese characters. The IME then provides the user with the most probable candidates corresponding to the typed phonetic spelling so that the user can choose the correct one.
Programmers have previously recognized the value of providing speech input into an IME. This is done by first converting the speech into text, which is then used as input into the IME. As has already been explained, however, the interpretation of speech is stochastic in nature. Hence, the text produced by the speech interpreter may not be the text that was intended by the user. If incorrect text is used as input into the IME, the results produced by the IME are likely to be poor. Accordingly, when speech is used as input into an IME, the program interpreting the speech data typically allows the user to first correct the text produced by the speech interpreter before inputting that text into the IME. When the IME produces foreign language translations of the text, the user may again choose the desired alternative because the result of an IME is also stochastic in nature. Requiring the user to edit the results at two different stages of the process can be inefficient and inconvenient. Thus, there is a further need in the art for an improved method of handling speech input to an IME.
SUMMARY OF THE INVENTION
The present invention meets the needs described above in a stochastic input combiner that facilitates the editing of text. The invention does this by providing alternatives for a text selection made by the user, even where that text selection is derived from multiple input sources, one or more of which can be stochastic in nature.
The stochastic input combiner provides the alternatives to the user in list form through a graphical user interface. The user can then choose one of the alternatives to replace the text selection the user has highlighted for editing. This can often be quicker than requiring the user to think of alternatives on his or her own and then make changes accordingly using a keyboard and mouse. If the user does not find an alternative the user likes for the text selection, the user can edit the text selection using the keyboard and mouse. In response, the stochastic input combiner can provide an updated list of alternatives that incorporate the user's changes. Often, the user need only partially edit the text selection before the stochastic input combiner produces an alternative the user likes, so the stochastic input combiner again improves editing efficiency.
The stochastic input combiner may also provide the advantage of a natural language model. Such a model may analyze the text selection as a whole using natural language principles in order to provide a better list of alternatives for the text selection. This, too, improves the user's editing efficiency.
Generally described, the present invention includes a method for correcting text. The user first enters text into the computer, perhaps using multiple stochastic input sources. The user may also use a keyboard and mouse to enter text into the computer.
Keyboard/mouse entry of text is an example of an input source which is non-stochastic, meaning that the text intended to be entered through the source can be determined with complete accuracy. On the other hand, a stochastic input source is one that converts input into a list of alternatives, each having less than 100% probability of being the correct alternative. Because speech cannot always be interpreted by a computer with complete accuracy, a speech recognition unit is an example of a stochastic input source which converts speech input into a list of text alternatives. Other examples of a stochastic input source include a handwriting recognition unit and an input method editor (IME). Where an input source for a text component is stochastic, the most likely alternative for the text component is generally used to represent the text component in the text selection.
Once the user enters text into the computer, the user can begin the correction process by making a text selection of a portion of the text the user entered. This text selection can include multiple text components. Such a text component can be a subset of the text selection that the user entered through a single input source. The user may have entered different text components within the text selection using different input sources, and the user may have entered one or more of the text components with a stochastic input source.
Once the user makes a text selection, the user may enter a command to display alternatives for the text selection as a whole. The stochastic input combiner then parses the text selection into its text co
Kim Paul Kyong Hwan
Reynar Jeffrey C.
Rucker Erik
Bashore William L.
Merchant & Gould
Shah Sanjiv
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