Showing papers by "NICE Systems published in 2016"

System and method for analysis of interactions with a customer service center

Abstract: A system and method for analysis of interactions with a customer service center, comprising receiving a plurality of customer service interactions, receiving a word cloud computed for the plurality of customer service interactions, consolidating similar or synonymous words into word sets, constructing a weighted graph of the word sets, generating a query for the interaction topic based on a corresponding subset of word sets, selecting at least one representative interaction from the retrieved customer service interactions, and displaying at least a portion of the representative interaction for the selected identified topic.

Systems and methods for offer selection and reward distribution learning

Abstract: Methods and systems for selecting an offer from a set of offers to be served to one or more respondents. In some embodiments, for each of the offers, an expected reward distribution is obtained comprising an estimate of the distribution over time of reward received in response to the offer. Requests are received for the selection of an offer and in response to each request an offer is selected with the selection depending at least partially on the expected reward distribution. The expected reward distributions are updated in repeated update operations after the initial serving of each offer, the updating being based on an observed distribution of reward received in response to the servings of the offer. The updated expected reward distribution is then used in the next selection of an offer. Update operations may take place before a complete set of response data is received.

Method and system for speech detection

Abstract: A system and method for determining an amount of speech in an audio signal may include for example: obtaining segments of the audio signal, wherein the segments are grouped into blocks; for each one of the segments, calculating a segment value indicative of an amplitude of the audio signal of a respective segment; for each one of the blocks calculating a block value indicative of the amplitude of the audio signal of a respective block; and calculating an audio signal speech grade based on segment values and block values, wherein the audio signal speech grade is indicative of the amount of speech in the audio signal.

Cross-language phoneme mapping for phonetic search keyword spotting using multiple source languages

Abstract: Performing Phonetic Search Keyword Spotting (PS KWS) in new languages when language resources are scarce is an interesting and challenging task. In a previous paper we reported a methodology that enabled PS KWS under these conditions utilizing cross-language phoneme mappings from another sufficiently resourced and well-trained source language. We performed phoneme recognition in the new target language with the acoustic model of the source language. The keyword search was performed over a phoneme lattice of the target language phonemes following a mapping from one language to the other. In the present work we extend this method and its capabilities by mapping two source language phoneme sets into one target language set and performing a combined lattice search. Testing the technique on English and Arabic as source languages yielded a 50% Detection Rate (DR) and a False Alarm Rate (FAR - measured in number of false alarms per hour per keyword) of 2 when Spanish was the target language, a DR of 36% and FAR of 4 when Dari was the target language and a DR of 35% and FAR of 6 with Farsi as the target language. These results indicate that combining two source languages is better than using a single language since the acoustic space is better represented. Searching in a combined lattice while employing adequate phoneme transformations significantly improves performance. Such a system can be used as an initial version of a PS KWS system in a new language when sufficient language resources are not available.

Determination of prominent phrases in multi-channel interactions by multi-feature evaluations

Abstract: A method for determining prominent keyphrases in interactions, comprising, receiving keyphrases of numerous interactions received via a plurality of channels that comprise apparatuses for conveying the interactions according to the media thereof, quantitatively evaluating each keyphrase by a plurality of different metrics thereby yielding a corresponding plurality of values, and linearly combining the plurality of the values with a corresponding plurality of coefficients associated with a channel via which an interaction having said keyphrase is received, thereby providing a score of said keyphrase, and based on a condition related to the scores of the keyphrases, selecting at least one keyphrase as an at least one prominent keyphrase, wherein the method is at least partially performed by an at least one computerized apparatus configured for interfacing with the apparatuses of the plurality of the channels.

Quality-dependent playback of recordings

Abstract: Responsive to concurrently recording on a plurality of recorders a telephonic interaction constructing a plurality of playlists, and according to faults identified while recording the plurality of playlists evaluating a quantitative quality score for each playlist in the plurality of playlists and presenting the playlists in a prioritized order according to the scores thereof.

System and method for resolving user identification

Abstract: A system and method obtain a recording of an interaction with a user and a screen recording related to the interaction; extract, from the screen recording, a unique identification value related to the user; resolve the identity of the user using the extracted unique identification value; and associate the user with the recorded interaction by associating the unique identification value with the interaction.

System and method for detecting and monitoring screen connectivity malfunctions

Abstract: A system and method for detecting and monitoring screen connectivity malfunctions, and generating alerts regarding presence of connectivity malfunctions, while identifying the user interface element that caused the connectivity malfunction.