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Language Identification results explained

Relevance: 100%      Posted on: 2019-05-20

This article aims on giving more details about Language Identification scoring and hints on how to tailor Language Identification to suit best your needs. Scoring and results explanation When Phonexia Language Identification identifies a language in audio recording (or languageprint) using a language pack, it creates languageprint of the recording (if input is audio recording) compares that languageprint with each language in a language pack and calculates probability that these two languages are the same The final scores are returned as logarithms of these individual probabilities – i.e. as values from {-inf,0} interval – for each language in the language pack.…

Keyword Spotting results explained

Relevance: 100%      Posted on: 2019-06-12

This article aims on giving more details about Keyword Spotting outputs and hints on how to tailor Keyword Spotting to suit best your needs. Scoring Keyword Spotting works by calculating likelihoods that at a given spot occurs a keyword or just any other speech, and comparing those two likelihoods. The following scheme shows Background model for anything before the keyword (1), the Keyword model (2) and a Background model of any speech parallel with the keyword model (3). Models 2 and 3 produce two likelihoods – Lkw and Lbg (any speech = background). Raw score is calculated as log likelihood…

Speech To Text results explained

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

This article aims on giving more details about Speech To Text outputs and hints on how to tailor Speech To Text to suit best your needs. In the process of transcribing speech, the Speech To Text technology usually identifies multiple alternatives for individual speech segments, as multiple phrases can have similar pronunciations, possibly with different word boundaries, e.g. “eight tea machines” vs. “eighty machines”. The technology provides various output types which show only single or multiple transcription alternatives. For processing realtime streams, two result modes are supported – one mode provides complete transcription, second mode provides incremental results. Output types…

Speech Analytics Course (technical training)

Relevance: 43%      Posted on: 2017-05-18

The Speech Analytics course consists of the following modules. Please ask your Phonexia contact for detailed description. (YES = this part of the course is obligatory)   SAL course Required time [h] Block name Block description YES 0,5 Intro & Phonexia Portfolio Intro & Phonexia Portfolio YES 0,5 Project focus – Explain basic needs Discussion of partner project focused mainly on finalizing the training topics and agenda. YES 0,75 Application Design & Development – Licensing Presentation of types of licensing, and how to use the license file. YES 0,75 Technologies – Data gathering and Quality measurement – basic Description of…

Voice Biometrics Course (technical training)

Relevance: 21%      Posted on: 2017-05-18

The Voice Biometrics course consist of the following modules. Please ask your Phonexia contact for detailed description. (YES = this part is mandatory for course)   VBS course Required time [h] Block name Block description YES 0,5 Intro & Phonexia Portfolio Intro & Phonexia Portfolio YES 0,5 Project focus - Explain basic needs Partner project related discussion focused mainly to finalizing training topics and agenda YES 0,75 Apps Designing and Developing - Licensing Gives trainee knowledge about type of licensing, and how to use the license file YES 0,75 Technologies - Data gathering and Quality measurement - basic Data gathering…

Language Identification (LID)

Relevance: 21%      Posted on: 2020-07-09

Phonexia Language Identification (LID) will help you distinguish the spoken language or dialect. It will enable your system to automatically route valuable calls to your experts in the given language or to send them to other software for analysis. Phonexia uses state-of-the-art language identification (LID) technology based on iVectors that were introduced by NIST (National Institute of Standards and Technology, USA) during the 2010 evaluations. The technology is independent on text and channel. This highly accurate technology uses the power of voice biometrics to automatically recognize spoken language. Application areas Preselecting multilingual sources and routing audio streams/files to language dependent…

Speech To Text

Relevance: 21%      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…

How to convert STT confusion network results to one-best

Relevance: 21%      Posted on: 2020-04-06

Confusion Network output is the most detailed Speech Engine STT output as it provides multiple word alternatives for individual timeslots of processed speech signal. Therefore many applications want use it as the main source of speech transcription and perform eventual conversion to less verbose output formats internally. This article provides the recommended way to do the conversion. Time slots and word alternatives: The recommended algorithm for converting Confusion Network (CN) to One-best is as follows: loop through all CN timeslots from start to end in each timeslot, get the input alternative with highest score and if it's not <null/> or…

SPE3 – Releases and Changelogs

Relevance: 21%      Posted on: 2020-09-12

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 3.30.13 (09/11/2020) - DB v1401, BSAPI 3.30.13 Public release New: Updated STT and KWS model AR_XL to version 5.1.0 Speech Engine 3.32.0 (08/28/2020) - DB v1500, BSAPI 3.32.0 Non-public Feature Preview release New: Added support for Webhooks and WebSockets in stream processing New: Added support for preferred phrases in 5th generation of STT (see POST /technologies/stt or POST /technologies/stt/input_stream) New:…