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Hakkani-Tur
Dilek Hakkani-Tur, Fremont, CA US
| Patent application number | Description | Published |
|---|---|---|
| 20120290290 | Sentence Simplification for Spoken Language Understanding - Sentence simplification may be provided. A spoken phrase may be received and converted to a text phrase. An intent associated with the text phrase may be identified. The text phrase may then be reformatted according to the identified intent and a task may be performed according to the reformatted text phrase. | 11-15-2012 |
| 20120290293 | Exploiting Query Click Logs for Domain Detection in Spoken Language Understanding - Domain detection training in a spoken language understanding system may be provided. Log data associated with a search engine, each associated with a search query, may be received. A domain label for each search query may be identified and the domain label and link data may be provided to a training set for a spoken language understanding model. | 11-15-2012 |
| 20120290509 | Training Statistical Dialog Managers in Spoken Dialog Systems With Web Data - Training for a statistical dialog manager may be provided. A plurality of log data associated with an intent may be received, and at least one step associated with completing the intent according to the plurality of log data may be identified. An understanding model associated with the intent may be created, including a plurality of queries mapped to the intent. In response to receiving a natural language query from a user that is associated with the intent a response to the user may be provided according to the understanding model. | 11-15-2012 |
Dilek Z. Hakkani-Tur, Parsippany, NJ US
| Patent application number | Description | Published |
|---|---|---|
| 20090248416 | SYSTEM AND METHOD OF SPOKEN LANGUAGE UNDERSTANDING USING WORD CONFUSION NETWORKS - Word lattices that are generated by an automatic speech recognition system are used to generate a modified word lattice that is usable by a spoken language understanding module. In one embodiment, the spoken language understanding module determines a set of salient phrases by calculating an intersection of the modified word lattice, which is optionally preprocessed, and a finite state machine that includes a plurality of salient grammar fragments. | 10-01-2009 |
| 20090254344 | ACTIVE LABELING FOR SPOKEN LANGUAGE UNDERSTANDING - A spoken language understanding method and system are provided. The method includes classifying a set of labeled candidate utterances based on a previously trained classifier, generating classification types for each candidate utterance, receiving confidence scores for the classification types from the trained classifier, sorting the classified utterances based on an analysis of the confidence score of each candidate utterance compared to a respective label of the candidate utterance, and rechecking candidate utterances according to the analysis. The system includes modules configured to control a processor in the system to perform the steps of the method. | 10-08-2009 |
Dilek Z. Hakkani-Tur, Denville, NJ US
| Patent application number | Description | Published |
|---|---|---|
| 20090063145 | Combining active and semi-supervised learning for spoken language understanding - Combined active and semi-supervised learning to reduce an amount of manual labeling when training a spoken language understanding model classifier. The classifier may be trained with human-labeled utterance data. Ones of a group of unselected utterance data may be selected for manual labeling via active learning. The classifier may be changed, via semi-supervised learning, based on the selected ones of the unselected utterance data. | 03-05-2009 |
| 20110172999 | System and Method for Building Emotional Machines - A system, method and computer-readable medium for practicing a method of emotion detection during a natural language dialog between a human and a computing device are disclosed. The method includes receiving an utterance from a user in a natural language dialog, receiving contextual information regarding the natural language dialog which is related to changes of emotion over time in the dialog, and detecting an emotion of the user based on the received contextual information. Examples of contextual information include, for example, differential statistics, joint statistics and distance statistics. | 07-14-2011 |
| 20120232898 | SYSTEM AND METHOD OF PROVIDING AN AUTOMATED DATA-COLLECTION IN SPOKEN DIALOG SYSTEMS - The invention relates to a system and method for gathering data for use in a spoken dialog system. An aspect of the invention is generally referred to as an automated hidden human that performs data collection automatically at the beginning of a conversation with a user in a spoken dialog system. The method comprises presenting an initial prompt to a user, recognizing a received user utterance using an automatic speech recognition engine and classifying the recognized user utterance using a spoken language understanding module. If the recognized user utterance is not understood or classifiable to a predetermined acceptance threshold, then the method re-prompts the user. If the recognized user utterance is not classifiable to a predetermined rejection threshold, then the method transfers the user to a human as this may imply a task-specific utterance. The received and classified user utterance is then used for training the spoken dialog system. | 09-13-2012 |
Dilek Z. Hakkani-Tur, Morris Plains, NJ US
| Patent application number | Description | Published |
|---|---|---|
| 20080270130 | SYSTEMS AND METHODS FOR REDUCING ANNOTATION TIME - Systems and methods for annotating speech data. The present invention reduces the time required to annotate speech data by selecting utterances for annotation that will be of greatest benefit. A selection module uses speech models, including speech recognition models and spoken language understanding models, to identify utterances that should be annotated based on criteria such as confidence scores generated by the models. These utterances are placed in an annotation list along with a type of annotation to be performed for the utterances and an order in which the annotation should proceed. The utterances in the annotation list can be annotated for speech recognition purposes, spoken language understanding purposes, labeling purposes, etc. The selection module can also select utterances for annotation based on previously annotated speech data and deficiencies in the various models. | 10-30-2008 |
Dilek Zeynep Hakkani-Tur, Morris Plains, NJ US
| Patent application number | Description | Published |
|---|---|---|
| 20090198493 | System and Method for Unsupervised and Active Learning for Automatic Speech Recognition - A system and method is provided for combining active and unsupervised learning for automatic speech recognition. This process enables a reduction in the amount of human supervision required for training acoustic and language models and an increase in the performance given the transcribed and un-transcribed data. | 08-06-2009 |