Abstract: Disclosed is a speaker diarization process for determining which speaker is speaking at what time during the course of a conversation. The entire process can be most easily described in five main parts: Segmentation where speech/non-speech decisions are made; frame feature extraction where useful information is obtained from the frames; segment modeling where the information from the frame feature extraction is combined with segment start and end time information to create segment specific features; speaker decisions when the segments are clustered to create speaker models; and corrections where frame level corrections are applied to the information extracted.

Abstract: Systems, apparatus, computer-readable media, and methods to provide filtering and/or search based at least in part on semantic representations of words in a document subject to the filtering and/or search are disclosed. Furthermore key words for conducting the filtering and/or search, such as taboo words and/or search terms, may be semantically compared to the semantic representation of the words in the document. A common semantic vector space, such as a base language semantic vector space, may be used to compare the key word semantic vectors and the semantic vectors of the words of the document, regardless of the native language in which the document is written or the language in which the key words are provided.

Abstract: Obtaining and/or validating user credentials at client devices is described. A phrase may be generated based on one or more index values determined according to a function of time and a credential identifier identifying a user credential. The phrase may be output by the client device for validating the user credential.

Abstract: In an embodiment, a method comprises receiving, at a translation server, a request for translation services from a requesting device for text data associated with a token and a first language; retrieving, at the translation server, a translated version of the text data in a second language from a translation database storing automatically translated text data and manually translated text data, if the token matches a previously processed token; retrieving, at the translation server, the translated version of the text data in the second language from an automated translation service, if the token does not match the previously processed token; retrieving, at the translation server, the translated version of the text data in the second language from the manual translation service; and transmitting, at the translation server, one or more of the automatically translated text data and the manually translated text data to the requesting device.

Abstract: The present invention is to provide a system for sharing a screen and a method for sharing a screen to easily understand a work instruction even when it is difficult for the worker to catch a voice due to a surrounding noise etc. A system for sharing a screen including a screen transmitter device 100 providing screen data and one or more screen receiver devices 10, the screen transmitter device 100 sharing a screen with the screen receiver devices 10, the system receives a definition of the shared area to share screen display, receives a voice input, converts the input voice into text data by voice recognition, and displays both of screen data inside the shared area defined by the received definition and the converted text data in the shared area.

Abstract: A “running range normalization” method includes computing running estimates of the range of values of features useful for voice activity detection (VAD) and normalizing the features by mapping them to a desired range. Running range normalization includes computation of running estimates of the minimum and maximum values of VAD features and normalizing the feature values by mapping the original range to a desired range. Smoothing coefficients are optionally selected to directionally bias a rate of change of at least one of the running estimates of the minimum and maximum values. The normalized VAD feature parameters are used to train a machine learning algorithm to detect voice activity and to use the trained machine learning algorithm to isolate or enhance the speech component of the audio data.

Abstract: Techniques for combining the results of multiple recognizers in a distributed speech recognition architecture. Speech data input to a client device is encoded and processed both locally and remotely by different recognizers configured to be proficient at different speech recognition tasks. The client/server architecture is configurable to enable network providers to specify a policy directed to a trade-off between reducing recognition latency perceived by a user and usage of network resources. The results of the local and remote speech recognition engines are combined based, at least in part, on logic stored by one or more components of the client/server architecture.

Abstract: A method for providing a context awareness service is provided. The method includes defining a control command for the context awareness service depending on a user input, triggering a playback mode and the context awareness service in response to a user selection, receiving external audio through a microphone in the playback mode, determining whether the received audio corresponds to the control command, and executing a particular action assigned to the control command when the received audio corresponds to the control command.

Abstract: In an approach for evaluating performance of machine translation, a processor receives a first document in a source language. A processor translates the first document in the source language to a second document in a target language, based, at least in part, on a first quantity of information. A processor evaluates the second document in the target language, based, at least, on one or more aspects of the translation. A processor determines, based, at least in part, on the evaluation, the second document in the target language meets a predetermined threshold.

Abstract: In an approach for evaluating performance of machine translation, a processor receives a first document in a source language. A processor translates the first document in the source language to a second document in a target language, based, at least in part, on a first quantity of information. A processor evaluates the second document in the target language, based, at least, on one or more aspects of the translation. A processor determines, based, at least in part, on the evaluation, the second document in the target language meets a predetermined threshold.

Abstract: Systems, apparatus, computer-readable media, and methods to provide translation of words or phrases from an initial language to a target language using multiple pathways are disclosed. The multiple pathways may have independent or near independent errors and the use of multiple pathways may reduce the errors that may be encountered in semantic vector based language translation. Cost values may be determined for translation to various potential words in the target language based at least in part on the multiple translation pathways between the initial language and the final language. The cost values may be used to select from among the various potential words in the target language.

Abstract: A machine translation system can improve results of machine translations by employing preferred translations, such as human translated phrases. In some implementations, the machine translation system can use the preferred translations as heavily weighted training data when building a machine translation engine. In some implementations, the machine translation system can use the preferred translations as an alternate to a result that would have otherwise been produced by a machine translation engine. While it is infeasible to obtain human translations for all translation phrases, preferred translations can be used for problem phrases for which machine translation engines often produce poor translations. The machine translation system can identify problem phrases by assigning a quality score to each translation in a set of translations.

Abstract: A method for adapting a phonetic dictionary for peculiarities of a speech of an at least one speaker, comprising generating search pronunciations for a search term, retrieving audio sections from an audio database for each search pronunciation, audibly presenting to a person the audio sections of the speech of the at least one speaker, and updating the phonetic dictionary based on acceptability of the audio sections determined from judgments by the person regarding intelligibility of the audio sections in audibly pronouncing the provided at least one word, wherein the method is performed on an at least one computerized apparatus configured to perform the method.

Abstract: A method, computer program product, and system for adapting speech recognition of a user's speech is provided. The method includes receiving a first utterance from a user having a duration below a predetermined threshold, identifying at least one further utterance from the user that provides additional information, generating a concatenated utterance by concatenating the first utterance with the at least one further utterance, transmitting the concatenated utterance to a speech recognition server, receiving a transcription of the concatenated utterance from the speech recognition server that includes a transcription of the first utterance, and extracting the transcription of the first utterance from the transcription of the concatenated utterance. The transcription of the first utterance is based on the additional information provided by the at least one further utterance.

Abstract: Systems and methods are disclosed for predicting words using a structured stem and suffix n-gram language model. The systems and methods include determining, using a first n-gram word language model, a first probability of a stem based on a first portion of a previously-input word in the received input. Using a second n-gram language model, a second probability of a first suffix may be determined based at least on a second portion the previously-input word in the received input. Further, a third probability of a second suffix different from the first suffix may be determined using a third n-gram language model based at least on a third portion of the previously-input word in the received input. A fourth probability of a predicted word may be determined based on the first, second and third probabilities. One or more predicted words may be determined and provided as an output to the user.

Abstract: Methods and systems are described herein for generating an audible presentation of a communication received from a remote server. A presentation of a media asset on a user equipment device is generated for a first user. A textual-based communication is received, at the user equipment device from the remote server. The textual-based communication is transmitted to the remote server by a second user and the remote server transmits the textual-based communication to the user equipment device responsive to determining that the second user is on a list of users associated with the first user. An engagement level of the first user with the user equipment device is determined. Responsive to determining that the engagement level does not exceed a threshold value, a presentation of the textual-based communication is generated in audible form.

Abstract: Techniques are described for identifying book title sets. The techniques may include a first-pass comparison with other books to identify other candidate title sets. A second-pass comparison may then be performed with respect to the candidate title sets. The first-pass comparison may be based on book metadata such as titles and authorship. The second-pass comparison may include a more comprehensive content comparison, such as comparing the body text of the books.

Abstract: A system and methods is provided for providing SIP based voice transcription services. A computer implemented method includes: transcribing a Session Initiation Protocol (SIP) based conversation between one or more users from voice to text transcription; identifying each of the one or more users that are speaking using a device SIP_ID of the one or more users; marking the identity of the one or more users that are speaking in the text transcription; and providing the text transcription of the speaking user to non-speaking users.

Abstract: An apparatus for controlling a data rate in a data client for a digital audio broadcasting system includes a buffer for storing data, a codec for coding data, and a control module for controlling a bit rate of the codec in response to a level of the data in the buffer. A method performed by the apparatus is also included.

Abstract: Mechanisms are provided for performing tabular data correction in a document. The mechanisms receive a natural language document comprising a portion of content and analyze the portion of content within the natural language document to identify an erroneous sub-portion comprising an erroneous or missing item of information. The mechanisms generate a semantic signature for the erroneous sub-portion and generate a query based on the semantic signature. The mechanisms apply the query to a knowledge base to identify a candidate sub-portion of content. The mechanisms correct the erroneous sub-portion using the identified candidate sub-portion of content to generate a corrected natural language document.