Abstract:
A system, method and computer readable medium that generates a language model from data from a web domain is disclosed. The method may include filtering web data to remove unwanted data from the web domain data, extracting predicate/argument pairs from the filtered web data, generating conversational utterances by merging the extracted predicate/argument pairs into conversational templates, and generating a web data language model using the generated conversational utterances.
Abstract:
A computerized method is disclosed for presenting advertising data extracted from a video data stream, the method including storing a plurality of advertising data items extracted from the video data stream at an end user device; and displaying a plurality of sorted advertising indicator data items at the end user device, wherein each of the advertising indicator data items indicates one of the plurality of stored advertising data items. A system is disclosed for performing the method. A data structure is disclosed providing a functional and structural interrelationship between a processor in the system and data in the data structure.
Abstract:
Disclosed are systems, methods, and computer readable media for identifying an acoustic environment of a caller. The method embodiment comprises analyzing acoustic features of a received audio signal from a caller, receiving meta-data information based on a previously recorded time and speed of the caller, classifying a background environment of the caller based on the analyzed acoustic features and the meta-data, selecting an acoustic model matched to the classified background environment from a plurality of acoustic models, and performing speech recognition as the received audio signal using the selected acoustic model.
Abstract:
A system, method and computer readable medium that provides an automated web transcription service is disclosed. The method may include receiving input speech from a user using a communications network, recognizing the received input speech, understanding the recognized speech, transcribing the understood speech to text, storing the transcribed text in a database, receiving a request via a web page to display the transcribed text, retrieving transcribed text from the database, and displaying the transcribed text to the requester using the web page.
Abstract:
A portable communication device has a touch screen display that receives tactile input and a microphone that receives audio input. The portable communication device initiates a query for media based at least in part on tactile input and audio input. The touch screen display is a multi-touch screen. The portable communication device sends an initiated query and receives a text response indicative of a speech to text conversion of the query. The portable communication device then displays video in response to tactile input and audio input.
Abstract:
A system and method disclosed for using and updating a database of template responses for a live agent in response to user communications. The method includes computing an average string distance between each response from a live agent and a template, use to generate the response, modifying the computed average string distance based on a customer satisfaction score associated with each response and selecting a response that minimizes the computed average string distance and maximizes customer satisfaction. Upon receiving a further communication on a certain issue, the system presents a prototype response that has been added to the template database to the live agent for use in generating a response to the further communication that reduces handling time and increases customer satisfaction.
Abstract:
Disclosed is a method and system for identifying critical emails. To identify critical emails, a critical email classifier is trained from training data comprising labeled emails. The classifier extracts N-grams from the training data and identifies N-gram features from the extracted N-grams. The classifier also extracts salient features from the training data. The classifier is trained based on the identified N-gram features and the salient features so that the classifier can classify unlabeled emails as critical emails or non-critical emails.
Abstract:
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for generating a model for use with automatic speech recognition. These principles can be implemented as part of a streamlined tool for automatic training and tuning of speech, or other, models with a fast turnaround and with limited human involvement. A system configured to practice the method receives, as part of a request to generate a model, input data and a seed model. The system receives a cost function indicating accuracy and at least one of speed and memory usage, The system processes the input data based on seed model and based on parameters that optimize the cost function to yield an updated model, and outputs the updated model.
Abstract:
In accordance with one aspect of the present invention, an automated method of and system for generating a response to a text-based natural language message is disclosed. The method includes identifying a first selected input clause in a sentence in the text-based natural language message. Also, assigning a semantic tag to the first selected input clause and matching the semantic tag to a historical input tag. The historical input tag associated with a first previously generated response clause. Further; generating an output response message based on the historical response clause, the output response message derived from the historical input tag and a second previously generated response clause. The system includes means for performing the method steps.
Abstract:
Systems and methods are provided for a voice message to text system supporting targeted advertisements. Voice messages received from users are converted to raw text messages that are normalized to insert proper punctuation and extract entity information. The normalized text and entity information are processed to extract concepts, such as critical phrases, from the normalized text. Extracted concepts are then matched to advertisements on an advertisement database having user selection criteria. Advertisements having selection criteria matching the extracted concepts are transmitted to the users, and the advertisers that placed the advertisements are charged fees for the advertisements. User profile information and user context information can additionally be used to select advertisements for transmission to users.