Medallia, Inc.

Other

David Garrod

Richard Michael Nemes

Wayne Ramprashad

Mikhail Lotvin

Jay R Pascarella

A method and apparatus for performing storage and retrieval in an information storage system cache is disclosed that uses the hashing technique with the open-addressing method for collision resolution. Insertion, retrieval, and deletion operations are limited to a predetermined number of probes, after which it may be assumed that the table does not contain the desired data. Moreover, when using linear probing, the technique facilitates maximum concurrent, multi-thread access to the table, thereby improving system throughput, since only a relatively small section is locked and made unavailable while a thread modifies that section, allowing other threads complete access to the remainder of the table.

Methods and apparatus for information storage and retrieval using a caching technique with probe-limited open-address hashing

The invention relates to systems/methods that enable real-time monitoring/processing of contact center communications to provide timely, actionable analytic insights and real-time critical call alerts, while simultaneously providing best-in-class protection of sensitive customer information.

Real-time contact center speech analytics, with critical call alerts, deployed across multiple security zones

A speech redaction engine includes a natural language processing (NLP)-based content redaction module receives an automatic speech recognition (ASR) decoding of a decoded portion of said digitized speech signal and utilizes NLP techniques to determine whether it contains sensitive information that should be redacted, and an ASR confidence-based redaction module that receives a confidence indicator and utilizes said confidence indicator to determine, independent of said NLP-based content redaction module, whether said decoded portion contains one or more word(s) that were recognized with a confidence level that is below a threshold. The speech redaction engine includes means for redacting said decoded portion if the NLP-based content redaction module determines that said portion should be redacted, and means for redacting the one or more word(s) if the ASR confidence-based redaction module determines that the one or more word(s) have the confidence level that is below the threshold.

Use of ASR confidence to improve reliability of automatic audio redaction

A process for compressing an audio speech signal utilizes ASR processing to generate a corresponding text representation and, depending on confidence in the corresponding text representation, selectively applies more, less, or no compression to the audio signal. The result is a compressed audio signal, with corresponding text, that is compact and well suited for searching, analytics, or additional ASR processing.

ASR-enhanced speech compression

A compact, self-authenticating, and speaker-verifiable record of an audio communication involving one or more persons comprises a record, encoded on a non-transitory, computer-readable medium, that consists essentially of: a voiceprint for each person whose voice is encoded in the record; a plurality of transcription records, where each transcription record consists essentially of a computer-generated speech-to-text decoding of an utterance and voiceprint associating information that associates a speaker of the utterance with one of the voiceprints stored in the record; and self-authenticating information sufficient to determine whether any of the information encoded in the communication record has been altered.

Compact, verifiable record of an audio communication and method for making same

A method includes removing sensitive information from an audio recording. The method includes receiving a digitally encoded audio recording; transcoding, if necessary, the audio recording to a pre-defined audio format; identifying periods of voice in/activity in the audio recording; segregating the audio recording into a sequence of separated utterances or words; streaming the sequence of separated utterances or words to an ASR server; receiving, for each streamed utterance or word, an associated ASR decoding; receiving, for each ASR decoding, an associated confidence score indicative of a probability that the associated ASR decoding is correct; identifying for redaction; any ASR decoding that contains sensitive information, and any ASR decoding with a confidence score less than a redaction threshold; and preparing a redacted audio recording by eliminating or masking those word(s) and/or utterance(s) for which an associated ASR decoding was identified for redaction.

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Pittsburgh, PA, United States of America

David Garrod