Nice Systems Ltd.

Intel Corporation

Other

Nice Ltd

Moshe Wasserblat

Oren Pereg

Yuval Lubowich

Michel Assayag

Ezra Daya

Tzach Ashkenazi

Ronen Laperdon

Jonathan Mamou

Tomer Rider

Shahar Taite

Yaniv Zigel

Dan Eylon

Barak Eilam

Oren Yaakov Lewkowicz

Oren Shamir

Ilan Kor

Omer Gazit

Gudmundur Kristjansson

Cromwell Fraser

Dori Shapira

Ronit Ephrat

Bastiaan Schönhage

Alexander Sivak

Yaron Morgenstern

Michael E Deisher

Marsal Gavalda

Gennadi Lembersky

Maor Nissan

Ilan Freedman

Hadas Liberman Ben-Ami

Stas Margolis

Guillermo Perez

Moshe Avlagon

Shai Shermister

Eytan Bar

Ze'ev Rivlin

Gili Aharoni

Yifat Meidav

Eyal Hurvitz

Offer Hassidi

Lior Arussy

Dimitri Volsky

Zvika Moretzky

Vasudev Lal

Hila Lam

Merav Ben-Asher

Gabriel Amores

Beeri Mart

Yair Dolev

Talia Falik

Yizhak Idan

Loic Dufresne De Virel

Ido David David

Gadi Singer

Ana Paula Quirino Simoes

Vladislav Feigin

Phillip Howard

Erik Norden

Oz Fox-Kahana

Nagib Hakim

Tzachi Ashkenazi

Ohad Pollak

Sherrie Shammass

Daniël Te Winkel

Liron Aichel

Maya Gorodetsky

Arden Ma

Oded Kalchiem

Ishay Levi

Daniel Korat

Steve Logalbo

Adee Lavi

Lior Hadaya

Bram Nachtegaal

Oren Peleg

Zohar Tsfoni

Jeroen Vink

Gil Dobry

Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory are disclosed. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least estimate a first information extraction cost corresponding to retrieval of information from a local knowledge base, estimate a second information extraction cost corresponding retrieval of information from a remote knowledge base, select an information source based on the first and second estimated information extraction costs, query the selected information source, in response to determining that the selected information source was an external information source, store the queried information in the local knowledge base, organize the stored information in the local knowledge base, and return the queried information.

Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory

An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

Speech model personalization via ambient context harvesting

Technologies for detecting an end of a sentence in automatic speech recognition are disclosed. An automatic speech recognition device may acquire speech data, and identify phonemes and words of the speech data. The automatic speech recognition device may perform a syntactic parse based on the recognized words, and determine an end of a sentence based on the syntactic parse. For example, if the syntactic parse indicates that a certain set of consecutive recognized words form a syntactically complete and correct sentence, the automatic speech recognition device may determine that there is an end of a sentence at the end of that set of words.

Technologies for end-of-sentence detection using syntactic coherence

A system and method for syntactic re-ranking of possible transcriptions generated by automatic speech recognition are disclosed. A computer system accesses acoustic data for a recorded spoken language and generates a plurality of potential transcriptions for the acoustic data. The computer system scores the plurality of potential transcriptions to create an initial likelihood score for the plurality of potential transcriptions. For a particular potential transcription in the plurality of transcriptions, the computer system generates a syntactical likelihood score. The computer system creates an adjusted score for the particular potential transcription by combining the initial likelihood score and the syntactic likelihood score for the particular potential transcription.

Syntactic re-ranking of potential transcriptions during automatic speech recognition

Generally, this disclosure provides systems, devices, methods and computer readable media for adaptation of language models and semantic tracking to improve automatic speech recognition (ASR). A system for recognizing phrases of speech from a conversation may include an ASR circuit configured to transcribe a user's speech to a first estimated text sequence, based on a generalized language model. The system may also include a language model matching circuit configured to analyze the first estimated text sequence to determine a context and to select a personalized language model (PLM), from a plurality of PLMs, based on that context. The ASR circuit may further be configured to re-transcribe the speech based on the selected PLM to generate a lattice of paths of estimated text sequences, wherein each of the paths of estimated text sequences comprise one or more words and an acoustic score associated with each of the words.

Dynamic adaptation of language models and semantic tracking for automatic speech recognition

A system and method for real-time processing a signal of a voice interaction. In an embodiment, a digital representation of a portion of an interaction may be analyzed in real-time and a segment may be selected. The segment may be associated with a source based on a model of the source. The model may updated based on the segment. The updated model is used to associate subsequent segments with the source. Other embodiments are described and claimed.

System and method for real-time speaker segmentation of audio interactions

Various systems and methods for providing a repositionable video display on a mobile device, to emulate the effect of user-controlled binoculars, are described herein. In one example, one or more high resolution video sources (such as UltraHD video cameras) obtain video that is wirelessly broadcasted to mobile devices. The mobile device processes the broadcast based on the approximate location of the spectator's mobile device, relative to a scene within the field of view of the mobile device. The location of the mobile device may be derived from a combination of network monitoring, camera inputs, object recognition, and the like. Accordingly, the spectator can obtain a virtual magnification of a scene from an external video source displayed on the spectator's mobile device.

Interactive binocular video display

The subject matter discloses a method for trade interaction chain reconstruction comprising: identifying a swap deal, the swap deal includes two or more of the received interactions and involves two or more participants; selecting a first interaction of the received interactions, said first interaction involves at least two participants of the two or more participants, said first interaction is stored on a computerized device; obtaining a first plurality of interactions of the received interactions that involve the at least two participants of the two or more participants; determining a first plurality of relevance scores between the first plurality of interactions and the first interaction; and associating interactions of the first plurality of interactions to be relevant to the swap deal according to the determined first plurality of relevance scores.

Method and apparatus for trade interaction chain reconstruction

A system and method for receiving an initial search entry to search text data. The text data may be, for example, an N word lattice, transcribed by a text to speech engine. The difference between the initial search entry and one or more entries in the dictionary may be measured. One or more similar entries may be selected from the dictionary that have the smallest measures of difference to the initial search entry. The text data may be searched for the one or more selected similar entries. Each of the searched similar entries found in the text data may be displayed as a search result.

System and method for flexible speech to text search mechanism

The subject matter discloses a method two phase phonetic indexing and search comprising: receiving a digital representation of an audio signal; producing a phonetic index of the audio signal; producing phonetic N-gram sequence from the phonetic index by segmenting the phonetic index into a plurality of phonetic N-grams; and producing an inverted index of the plurality of phonetic N-grams.

Method and apparatus for enhanced phonetic indexing and search

The subject matter discloses a method for expansion of search queries on large vocabulary continuous speech recognition transcripts comprising: obtaining a textual transcript of audio interaction generated by the large vocabulary continuous speech recognition; generating a topic model from the textual transcripts; said topic model comprises a plurality of topics wherein each topic of the plurality of topics comprises a list of keywords; obtaining a search term; associating a topic from the topic model with the search term; and generating a list of candidate term expansion words by selecting keywords from the list of keywords of the associated topic; said candidate term expansion words are of high probability to be substitution errors of the search term that are generated by the large vocabulary continuous speech recognition.

Method and apparatus for expansion of search queries on large vocabulary continuous speech recognition transcripts

The subject matter discloses a computerized method for real time emotion detection in audio interactions comprising: receiving at a computer server a portion of an audio interaction between a customer and an organization representative, the portion of the audio interaction comprises a speech signal; extracting feature vectors from the speech signal; obtaining a statistical model; producing adapted statistical data by adapting the statistical model according to the speech signal using the feature vectors extracted from the speech signal; obtaining an emotion classification model; and producing an emotion score based on the adapted statistical data and the emotion classification model, said emotion score represents the probability that the speaker that produced the speech signal is in an emotional state.

Method and apparatus for real time emotion detection in audio interactions

A method and system for indicating in real time that an interaction is associated with a problem or issue, comprising: receiving a segment of an interaction in which a representative of the organization participates; extracting a feature from the segment; extracting a global feature associated with the interaction; aggregating the feature and the global feature; and classifying the segment or the interaction in association with the problem or issue by applying a model to the feature and the global feature. The method and system may also use features extracted from earlier segments within the interaction. The method and system can also evaluate the model based on features extracted from training interactions and manual tagging assigned to the interactions or segments thereof.

Methods and apparatus for real-time interaction analysis in call centers

A system and method for adapting a language model to a specific environment by receiving interactions captured the specific environment, generating a collection of documents from documents retrieved from external resources, detecting in the collection of documents terms related to the environment that are not included in an initial language model and adapting the initial language model to include the terms detected.

Method and system for automatic domain adaptation in speech recognition applications

Growing community of inventors

Maccabim, Israel

Moshe Wasserblat