NICE Systems

About: NICE Systems is a based out in . It is known for research contribution in the topics: Session (computer science) & Audio signal. The organization has 277 authors who have published 197 publications receiving 5264 citations.

System and method for text normalization in noisy channels

Abstract: Systems and methods for text normalization in a plurality of noisy channels receive a text entry and channel origin data of the text entry; determine whether the text entry matches an in-vocabulary (IV) entry or whether the text entry is an out-of-vocabulary (OOV) entry; if the text entry is determined to have a matching IV entry, output the matching IV entry, and if the text entry is determined to be an OOV entry, implement a channel-specific error-type adapter framework based on the channel origin data, wherein the channel-specific error-type adapter framework is optimized for a specific channel from which the text entry originated; normalize the text entry using the channel-specific error-type adapter framework; and output one or more candidate normalized forms of the text entry.

Cross-language phoneme mapping for phonetic search keyword spotting in continuous speech of under-resourced languages

Abstract: As automatic speech recognition-based applications become increasingly common in a wide variety of market segments, thereis a growing need to support more languages. However, for many languages, the language resources needed to train speechrecognition engines are either limited or completely non-existent, and the process of acquiring or constructing new languageresources is both long and costly. This paper suggests a methodology that enables Phonetic Search Keyword Spotting to beimplemented in a large speech database of any given under-resourced language using cross-language phoneme mappings toanother language. The phoneme mapping enables a speech recognition engine from a sufficiently resourced and well-trainedsource language to be used for phoneme recognition in the new target language. The keyword search is then performed overa lattice of target language phonemes. Three cross-language phoneme mapping techniques are examined: knowledge-based,data-driven and phoneme recognition performance-based. The results suggest that Phonetic Search Keyword Spotting basedon the cross-language phoneme mapping approach proposed herein can serve as a quick initial solution for validating keywordspotting applications in new, under-resourced languages.

System and method for phonetic search over speech recordings

Abstract: A system and method for searching for an element in speech related documents may include transcribing a set of speech recordings to a set of phoneme strings and including the phoneme strings in a set of phonetic transcriptions. A system and method may reverse-index the phonetic transcriptions according to one or more phonemes such that the one or more phonemes can be used as a search key for searching the phoneme in the phonetic transcriptions. A system and method may transcribe a textual search term into a set of search phoneme strings and use the set of search phoneme strings to search for an element in the set of phonetic transcriptions.

Method and system for scenario investigation

Abstract: According to embodiments of the present invention a computer implemented process for reconstruction of incidents handled by emergency service providers is provided. The method includes retrieving multimedia recorded events containing data related to an incident handled by an emergency service provider from a plurality of incident sources, reconstructing the incident on a client computer, organizing the incident and distributing the organized data.

System and method for sentiment lexicon expansion

Abstract: Systems and methods for sentiment lexicon expansion receive at least a domain specific corpus comprising a plurality of words, and a generic sentiment lexicon; parse the plurality of words in the domain specific corpus into a plurality of dependency relations; identify, using one or more syntactic dependency rules and at least one of the plurality of dependency relations, a set of one or more sentiment candidates in the domain specific corpus; filter from the set of one or more sentiment candidates any sentiment candidate having an expected performance below a predefined threshold; sample the filtered set of one or more sentiment candidates to be used in a qualitative evaluation; and, for each sentiment candidate that passes the qualitative evaluation, add the sentiment candidate to the generic sentiment lexicon.