| Class / Patent application number | Description | Number of patent applications / Date published |
|---|
| 704253000 | Endpoint detection | 12 |
| 20080262843 | SPEECH RECOGNITION APPARATUS AND METHOD - An apparatus and method for recognizing paraphrases of uttered phrases, such as place names. At least one keyword contained in a speech utterance is recognized. Then, the keyword(s) contained in the speech utterance are re-recognized using a phrase including the keyword(s). Based on both recognition results, it is determined whether a paraphrase could have been uttered. If a paraphrase could have been uttered, a phrase corresponding to the paraphrase is determined as a result of speech recognition of the speech utterance. | 10-23-2008 |
| 20090037176 | CONTROL AND CONFIGURATION OF A SPEECH RECOGNIZER BY WORDSPOTTING - A wordspotting system is applied to a speech source in a preliminary processing phase. The putative hits corresponding to queries (e.g., keywords, key phrases, or more complex queries that may include Boolean expressions and proximity operators) are used to control a speech recognizer. The control can include one or more of application of a time specification that is determined from the putative hits for selecting an interval of the speech source to which to apply the speech recognizer; application of a grammar specification determined from the putative hits that is used by the speech recognizer, and application of a specification of a lattice or pruning specification that is used by the recognizer to limit or guide the recognizer in recognition of the speech source. | 02-05-2009 |
| 20090063150 | METHOD FOR AUTOMATICALLY IDENTIFYING SENTENCE BOUNDARIES IN NOISY CONVERSATIONAL DATA - Sentence boundaries in noisy conversational transcription data are automatically identified. Noise and transcription symbols are removed, and a training set is formed with sentence boundaries marked based on long silences or on manual markings in the transcribed data. Frequencies of head and tail n-grams that occur at the beginning and ending of sentences are determined from the training set. N-grams that occur a significant number of times in the middle of sentences in relation to their occurrences at the beginning or ending of sentences are filtered out. A boundary is marked before every head n-gram and after every tail n-gram occurring in the conversational data and remaining after filtering. Turns are identified. A boundary is marked after each turn, unless the turn ends with an impermissible tail word or is an incomplete turn. The marked boundaries in the conversational data identify sentence boundaries. | 03-05-2009 |
| 20100114576 | SOUND ENVELOPE DECONSTRUCTION TO IDENTIFY WORDS IN CONTINUOUS SPEECH - A speech recognition capability in which words of spoken text are identified based on the contour of sound waves representing the spoken text. Variations in the contour of the sound waves are identified, features are assigned to those variations, and then the features are mapped to sound constructs to provide the words. | 05-06-2010 |
| 20100332230 | PHONETIC DISTANCE MEASUREMENT SYSTEM AND RELATED METHODS - Phonetic distances are empirically measured as a function of speech recognition engine recognition error rates. The error rates are determined by comparing a recognized speech file with a reference file. The phonetic distances can be normalized to earlier measurements. The phonetic distances/error rates can also be used to improve speech recognition engine grammar selection, as an aid in language training and evaluation, and in other applications. | 12-30-2010 |
| 20120265530 | Speech End-Pointer - A rule-based end-pointer isolates spoken utterances contained within an audio stream from background noise and non-speech transients. The rule-based end-pointer includes a plurality of rules to determine the beginning and/or end of a spoken utterance based on various speech characteristics. The rules may analyze an audio stream or a portion of an audio stream based upon an event, a combination of events, the duration of an event, or a duration relative to an event. The rules may be manually or dynamically customized depending upon factors that may include characteristics of the audio stream itself, an expected response contained within the audio stream, or environmental conditions. | 10-18-2012 |
| 20130325475 | APPARATUS AND METHOD FOR DETECTING END POINT USING DECODING INFORMATION - An apparatus for detecting an end point using decoding information includes: an end point detector configured to extract a speech signal from an acoustic signal received from outside and detect end points of the speech signal; a decoder configured to decode the speech signal; and an end point detector configured to extract reference information serving as a standard of actual end point discrimination from decoding information generated during the decoding process of the decoder, and discriminate an actual end point among the end points detected by the end point detector based on the extracted reference information. | 12-05-2013 |
| 20150051911 | METHOD FOR DIVIDING LETTER SEQUENCES INTO PRONUNCIATION UNITS, METHOD FOR REPRESENTING TONES OF LETTER SEQUENCES USING SAME, AND STORAGE MEDIUM STORING VIDEO DATA REPRESENTING THE TONES OF LETTER SEQUENCES - Disclosed is a method for dividing pronunciation units which includes the steps of: extracting voice-intensity maxima and minima in voice waveforms of letter sequences; forming a group by grouping the extracted maxima together; dividing the letter sequences into pronunciation units around the points nearest to either side of the group from among minima on both sides of the group, voice start points, and voice end points. | 02-19-2015 |
| 20150302849 | System And Method For Identifying Special Information - A system and method for identifying special information is provided. Endpoints are defined within a voice recording. One or more of the endpoints are identified within the voice recording and the voice recording is partitioned into segments based on the identified endpoints. Elements of text are identified by applying speech recognition to each of the segments and a list of prompt list candidates are applied to the text elements. The segments with text elements that match one or more prompt list candidates are identified. Portions of the voice recording following the prompt list candidates that include special information are identified and the special information is rendered unintelligible within the voice recording. | 10-22-2015 |
| 20160026618 | SYSTEM AND METHOD OF EXTRACTING CLAUSES FOR SPOKEN LANGUAGE UNDERSTANDING - A clausifier and method of extracting clauses for spoken language understanding are disclosed. The method relates to generating a set of clauses from speech utterance text and comprises inserting at least one boundary tag in speech utterance text related to sentence boundaries, inserting at least one edit tag indicating a portion of the speech utterance text to remove, and inserting at least one conjunction tag within the speech utterance text. The result is a set of clauses that may be identified within the speech utterance text according to the inserted at least one boundary tag, at least one edit tag and at least one conjunction tag. The disclosed clausifier comprises a sentence boundary classifier, an edit detector classifier, and a conjunction detector classifier. The clausifier may comprise a single classifier or a plurality of classifiers to perform the steps of identifying sentence boundaries, editing text, and identifying conjunctions within the text. | 01-28-2016 |
| 20160198234 | SYSTEMS, COMPUTER-IMPLEMENTED METHODS, AND TANGIBLE COMPUTER-READABLE STORAGE MEDIA FOR TRANSCRIPTION ALIGNMENT | 07-07-2016 |
| 20160379632 | LANGUAGE MODEL SPEECH ENDPOINTING - An automatic speech recognition (ASR) system detects an endpoint of an utterance using the active hypotheses under consideration by a decoder. The ASR system calculates the amount of non-speech detected by a plurality of hypotheses and weights the non-speech duration by the probability of each hypotheses. When the aggregate weighted non-speech exceeds a threshold, an endpoint may be declared. | 12-29-2016 |
