Search Results for: reaction times

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Keyword Spotting (KWS)

Relevance: 100%      Posted on: 2017-05-18

About KWS Phonexia Keyword Spotting (KWS) identifies occurrences of key-words and/or key-phrases in audio recordings. Application areas: Security/defense Maintain fast reaction times by routing calls with specific content to human operators Search for specific information in large call archives Trigger alarms immediately (online) when an event occurs Call centers Increase operator and supervisor efficiency by searching calls Identify inappropriate expressions from operators Check marketing campaigns with automatic script compliance control Mass media and web search servers Index and search multimedia by keyword Route multimedia files and streams according to their content   KWS technology Acoustic based technology robust even with…

Speech To Text

Relevance: 100%      Posted on: 2019-05-27

Phonexia Speech To Text – also known as a voice-to-text or speech recognition – converts speech signals into plain text. After the conversion, text can be easily read, edited, searched, processed by text-based data mining tools or archived. Phonexia Speech To Text is optimized for noisy recordings and colloquial speech, can process audio files as well as audio streams and can provide results in several output formats. Typical use cases look for specific information in large call archives (e.g., claims inspection) get additional value by advanced analysis of call traffic (e.g., topic detection) maintain short reaction times by routing calls…

Time Analysis (TAE)

Relevance: 100%      Posted on: 2017-05-18

Technology description Technology Time Analysis Extraction by Phonexia extracts base information from dialogue in a recording, providing essential knowledge about conversation flow. That makes it easy to identify long reaction time, crosstalk, or responses of speakers in both channels.  This technology is only meaningful when used on recordings with 2 channels. As an answer to the TAE technology, SPE returns a json/xml file. This file includes general information about the technology and details of the time analysis. The technology can work either with a closed recording or with a stream. Monologue Describes the statistics of a recording related to one…

Time Analysis

Relevance: 100%      Posted on: 2018-04-15

Time Analysis Extraction (TAE) by Phonexia extracts base information from dialogue in a recording, providing essential knowledge about conversation flow. That makes it easy to identify long reaction time, crosstalk, or responses of speakers in both channels. This technology is only meaningful when used on recordings with 2 channels. As an answer to the TAE technology, SPE returns a json/xml file. This file includes general information about the technology and details of the time analysis. The technology can work either with a closed recording or with a stream. Monologue Describes the statistics of a recording related to one channel. channel…

Keyword Spotting

Relevance: 100%      Posted on: 2019-06-03

Phonexia Keyword Spotting (KWS) identifies occurrences of keywords and/or keyphrases in audio recordings. It can help you to get valuable information from huge quantities of speech recordings. You only need to specify the keywords or phrases you wish to find. This technology identifies all recordings with keyword occurrences and allows you to automatically route important recordings or calls to your experts. Typical use cases Call centers increase operator and supervisor efficiency by searching calls identify inappropriate expressions from operators check marketing campaigns with automatic script-compliance control Mass media and web search servers index and search multimedia by keyword route multimedia…

Software Vetting

Relevance: 50%      Posted on: 2018-04-06

The purpose of this document is to help client to satisfy their high security standards during integration of Phonexia software to their critical infrastructure. The vetting ensures that Phonexia software is not dangerous to the client’s infrastructure in any way. It means there are no backdoors, viruses, worms, Trojan horses, spyware, adware, critical bugs, unwanted functionality, no information is sent outside the client’s infrastructure. Vetting context Speech technology is a very dynamic area with a very fast development. For example the speaker identification error rate decreases to half between each two evaluations organized by National Institute of Standards and Technology,…

Voice Inspector

Relevance: 50%      Posted on: 2017-05-18

About Phonexia Voice Inspector v3 (VIN3) provides police forces and forensic experts with a highly accurate speaker identification tool during investigation of criminal matters. It uses the power of voice biometry to automatically recognize speakers by their voice. Main features of the VIN3 application: Automatic speaker identification tool to strengthen results of the standard phonetics-based approaches Scoring in likelihood ratio (LR) – Result from statistical test for two models comparison. It gives back number which expresses how many times more likely the data are under one model than the other. LnLR or LogLR meets numbers in interval <-∞;+∞>...), and verbal…

Software Vetting (Best Practice)

Relevance: 50%      Posted on: 2017-06-15

The purpose of this document is to help client to satisfy their high security standards during integration of Phonexia software to their critical infrastructure. The vetting ensures that Phonexia software is not dangerous to the client’s infrastructure in any way. It means there are no backdoors, viruses, worms, Trojan horses, spyware, adware, critical bugs, unwanted functionality, no information is sent outside the client’s infrastructure. Vetting context Speech technology is a very dynamic area with a very fast development. For example the speaker identification error rate decreases to half between each two evaluations organized by National Institute of Standards and Technology,…

SPE3 – Releases and Changelogs

Relevance: 50%      Posted on: 2020-03-26

Speech Engine (SPE) is developed as RESTfull API on top of Phonexia BSAPI. SPE was formerly known as BSAPI-rest (up to v2.x) or as Phonexia Server (up to v3.2.x). This page lists changes in SPE releases. Releases Changelogs Speech Engine 3.30.0 (03/25/2020) - DB v1400, BSAPI 3.30.0 Public release New: Added 5th generation of FR_FR of STT, KWS and PHNREC New: Updated and significantly improved phonemes document for STT and KWS (see doc directory) New: Added n-best output to all 5th generation STT stream results New: Added support for native numbers and dates notation in n-best output in 5th generation CS_CZ…

Q: What LLR, LR and score mean?

Relevance: 50%      Posted on: 2017-06-27

A: These abbreviations mean the following: LR - likelihood ratio, result from statistical test for two models comparison. It returns a number which expresses how many times more likely the data are under one model than the other.  LR meets numbers in interval <0;+inf). LLR - abbreviation for log-likelihood ratio statistic, logarithmic function of LR. LLR meets numbers in interval (-inf;+inf). Percentage (normalised) score - commonly used mathematical transformation of the LLR to percentage. This number is better for human readability but may bring some doubts if LLR numbers are too high (typically for some non-adapted installations). Interval <0;100> (or…