795 results about "Punctuation" patented technology

A speech recognition system and method operates a speech recognition application on a computer in a continuous dictation mode. A separate key pad is coupled to the computer through the USB port, and includes a plurality of keys for providing command signals representative of a desired computer operation command which override the dictation mode of the speech recognition application whenever such a command is operated. This allows the user to insert commands, such as punctuation, numerals, “next line”, “next paragraph”, and the like, directly from the key pad while maintaining operation of the voice recognition application in its continuous dictation mode.

Speech recognition is performed in near-real-time and improved by exploiting events and event sequences, employing machine learning techniques including boosted classifiers, ensembles, detectors and cascades and using perceptual clusters. Speech recognition is also improved using tandem processing. An automatic punctuator injects punctuation into recognized text streams.

In a speech recognition system which recognizes a spoken utterance consisting of a sequence of spoken words and, in response, outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words is provided. In a vocabulary of items including words, silences, and punctuation marks, assigning at least one baseform to each punctuation mark corresponding to one of silence and a non-word noise. Additionally, the method includes the step of automatically inserting a subject punctuation mark at a given point in the sequence of decoded words when an acoustic score and a language model score associated with the subject punctuation mark produce a higher combined likelihood than the acoustic score and the language model score associated with any other item in the vocabulary for the given point in the sequence of decoded words.

Described herein is a computer-implemented system and method for processing one or more alternate symbols associated or linked to a base symbol. A base symbol is a symbol to which at least one alternate symbol is linked. A base symbol commonly appears on a key of a keyboard or a display of a keyboard, or is a handwritten symbol recognized by handwriting entry software. Examples of alternate symbols are accented characters and punctuation marks that do not appear on a keyboard or are not commonly recognized by a handwriting entry program, and short symbol sequences. An example of a common short symbol sequence is an emoticon used in e-mail messages to convey tone or feelings. An example of a computer device that may embody the system or method is a hand-held computing device.

The invention relates to an intelligent error correction system of key words in the process of searching networks and a method thereof. On an Internet platform, firstly, a related linguistic model and a corresponding dictionary as well as a data index database are established through the training of related data information; secondly, a text is inputted, a Pinyin error correction part calculates the mistakes of Pinyin and characters, the error correction of characters is calculated by a fuzzy match; finally, all results are filtered according to the degree of association, a plurality of results are sorted to get the proximal results. The polyphone mistakes and character types as well as word types mistakes inputted by a user are corrected by means of the sound-character conversion and fuzzy error correction technical methods to correct the character replace mistakes, the unwanted character or the leakage of character mistakes, the character position mistakes, etc. in the input process. Moreover, the basic functions are expanded on the basis such as the English-Chinese and punctuations mixing error correction, the fuzzy match technique, the related prompt technique and the enhanced intelligence error correction.

The invention relates to the technical field of speech recognition and discloses a method and system for realizing automatic addition of punctuation marks in the speech recognition. The method comprises the steps of: collecting user speech signals; carrying out the speech recognition on the user speech signals so as to generate a character sequence containing a plurality of sentences; sequentially calculating duration of pause positions between the sentences in the character sequence; if the duration is less than a preset threshold value, adding commas at the pause positions; and if the duration is greater than or equal to the preset threshold value, confirming the mood types of the sentences in front of the pause positions by utilizing a pre-generated classifier and adding punctuation marks at the pause positions according to the types. By utilizing the method and system which are provided by the invention, the automatic addition of the punctuation marks can be simply and conveniently realized and the accuracy and the flexibility of adding the punctuation marks are increased.

A method based on Chinese website punctuation triple recognition and text content filtering. The method based on existing URL, the website information keywords in the method of filtration - filtration rate and the low rate of filtration of the whole problem, Bringing on a method for composite based on the URL and on keywords, as well as text-based knowledge representation method of vector space website text content filtering. Applying to a method Based on black-and-white list of URL filtering and Chinese punctuation statistical characteristics to effectively remove navigation information, relevant linked information, advertising linked information, copyright information and other Web content noise information to extract content of text; adopting vector space model text knowledge representation, By calculating vector text template and unhealthy information in the feature vector cosine angle, and set the threshold, compared to the text of the class. The invention can be widely used in the filtering of undesirable information network and website personalized information services.

The invention discloses network criticism oriented viewpoint subject identifying method and system. The method comprises the following steps of: a. text inputting: inputting a criticism source and all criticism texts; b. text preprocessing: carrying out word division and speech part marking on the input texts, removing stop words, punctuations and specific empty words and calculating the word frequency information of the words; c. subject word judgment: calculating a word weight value, and if the word weight value is larger than a set threshold value, judging that a subject word is a viewpoint subject word; d. subject constructing: combining scattered viewpoint subject words into an integrated viewpoint subject; e. subject screening: confirming an effective viewpoint subject by filtering the viewpoint subject. The invention overcomes the field limitation of viewpoint analyzing method and system, identifies the viewpoint subject in a whole angle without constructing a body library, effectively overcomes the difficulty existing in single-sentence viewpoint analysis and automatically identifies the viewpoint subject in a phrase mode of a wide field and network criticism data which are dynamically changed along with the time.

A system and method related to a new approach to speech recognition that reacts to concepts conveyed through speech. In its fullest implementation, the system and method shifts the balance of power in speech recognition from straight sound recognition and statistical models to a more powerful and complete approach determining and addressing conveyed concepts. This is done by using a probabilistically unbiased multi-phoneme recognition process, followed by a phoneme stream analysis process that builds the list of candidate words derived from recognized phonemes, followed by a permutation analysis process that produces sequences of candidate words with high potential of being syntactically valid, and finally, by processing targeted syntactic sequences in a conceptual analysis process to generate the utterance's conceptual representation that can be used to produce an adequate response. The invention can be employed for a myriad of applications, such as improving accuracy or automatically generating punctuation for transcription and dictation, word or concept spotting in audio streams, concept spotting in electronic text, customer support, call routing and other command/response scenarios.

Methods and systems for processing text or character data are disclosed. A text processing system receives a character input string and determines whether to apply character processing. A non-English language such as Italian can be entered into a processing system such as a computer using a standard English based keyboard such that additional keys for providing accents or other grammatical and punctuation symbols or characters not existing in English are unnecessary. In one mode, text is automatically accented or punctuated without requiring user intervention. In another mode, a user is provided with a list of accent or punctuation choices so that the user may select the optimum accent or punctuation. Text processing of an input may be activated by a predefined activator key pressed in a predetermined sequence, or may be activated in the event a predetermined sequence of characters is received.

A text enhancement method and apparatus for the presentation of text for improved human reading. The method includes extracting text specific attributes from machine readable text and varying the text presentation in accordance with the attributes. The preferred embodiment of the method: extracts parts of speech and punctuation from a sentence, applies folding rules which use the parts of speech to determine folding points, and presents text segments each on a new line and having a determined horizontal displacement based on the text specific attributes. One method displays text over bent curves having a shape based on text content. Another method includes displaying relative text position within a hierarchy using alternating vertically and horizontally tiled planes. Another method supports reading text segments across opposed pages without waiting for paging. Yet another method displays text to allow reading from bottom to top as though from front to back. Still another method displays words in colors reflecting the relationships between the words and the larger text segments of which they are apart.

A technique for compressing texts such that referential integrity, sentence coherency, punctuation and readability are preserved and which provides for compression of sentence constituents based on the type of content, the informativity of the sentence constituent and the grammatical readability of the resultant sentence or phrase. Information content portions are parsed to generate parts of speech tags. The informativity of the constituents in a phrase or sentence is determined and the parts of speech having lower information content and having a low effect on grammatical readability of the phrase or sentence are selectively compressed. Parts of speech having successively higher informativity and low effect on grammatical readability are selected for compression until the desired level of compression is reached. Compressed portions are indicated in the summary with a selectable placeholder which expands to display the compressed text.

A specially-configured interactive user interface for use in eye typing takes the form of a three-layer arrangement that allows for controlling computer input with eye gazes. The three-layer arrangement includes an outer, rectangular ring of letters, displayed clockwise in alphabetical order (forming the first layer). A group of “frequently-used words” associated with the letters being typed forms an inner ring (and is defined as the second layer). This second layer of words is constantly updated as the user continues to enter text. The third layer is a central “open” portion of the interface and forms the typing space—the “text box” that will be filled as the user continues to type. A separate row of control/function keys (including mode-switching for upper case vs. lower case, numbers and punctuation) is positioned adjacent to the three-layer on-screen keyboard display.

The invention discloses a Chinese domain term recognition method based on mutual information and a conditional random field model. The Chinese domain term recognition method includes the following steps: (1) gathering domain text corpus and marking all the punctuations, spaces, numbers, ASSCII (American Standard Code for Information Interchange) characters and characters except Chinese characters in the corpus; (2) setting character strings and computing the mutual information values of the character strings, (3) computing the left comentropy and the right comentropy of every character string, (4) defining character string evaluation function, setting evaluation function threshold, computing the evaluation function values of every character string, determining that every character string is a word, comparing in sequence the evaluation function value of the former character with the evaluation function value of the latter character in the character string and segmenting character meaning character strings one by one, (5) utilizing conditional random fields to train a conditional random field model and recognizing domain terms with the conditional random field model. When the Chinese domain term recognition method is used to recognize terms, the data sparsity of legitimate terms is overcome, the amount of calculation of conditional random fields is reduced, and the accuracy of the Chinese domain term recognition is improved.

Non-verbalized tokens, such as punctuation, are automatically predicted and inserted into a transcription of speech in which the tokens were not explicitly verbalized. Token prediction may be integrated with speech decoding, rather than performed as a post-process to speech decoding.

The present invention pertains to a system and method for the tokenization of text. The featurizer may be configured to receive input text and convert the input text into tokens. According to one aspect of the invention, the tokens may include only one type of character, the characters selected from the group consisting of letters, numbers, and punctuation. The tokenizer may also include a classifier. The classifier may be configured to receive the tokens from the featurizer. Furthermore, the classifier may be configured to analyze the tokens received from the featurizer to determine if the tokens may be input into a predetermined classification model using a preclassifier. If one of the tokens passes the preclassifier, then the token is classified using the predetermined classification model. Additionally, according to a first aspect of the invention, the tokenizer may also include a finalizer. The finalizer may be configured to receive the tokens and may be configured to produce a final output.