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SPE3 – Releases and Changelogs

     Posted on: 2021-04-16

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). Releases Changelogs Speech Engine 3.40.1, DB v1700, BSAPI 3.40.1 (2021-04-16) Public release Fixed: 6th generation STT/KWS stream result may start with words from end of previous stream Fixed: Some licensing error messages are not shown in log Fixed: Missing file names in log messages in SID and SID4 tasks Fixed: Keyword list may not work if XML is used as input and optional fields threshold or pronunciations are used Fixed: phxdamin2…

Browser3 – Releases and Changelogs

     Posted on: 2021-04-06

Phonexia Browser v3 (Browser3) is developed as client on top of Phonexia Speech Engine v3. Phonexia Browser is a successor of Phonexia Speech Intelligence Resolver v1 (SIR1). This page lists changes in Browser releases. Releases Changelogs Phonexia Browser 3.40.0, BSAPI 3.40.0 (2021-03-26) Public release New: Compatibility with SPE 3.40 Changed: Using new licensing system under the hood (internal change) NOTE: When using Browser with FLS (Floating License Server), you need to upgrade FLS to version 2.x in order to be able to use Browser 3.40+ with FLS. Phonexia Browser v3.30.13, BSAPI 3.30.14 (2021-03-25) Public release Fixed: One more issue in…

Speech Engine 3.35.4

     Posted on: 2020-12-14

Speech Engine 3.35.4, DB v1601, BSAPI 3.35.4 (2020-12-14) Fixed STT/KWS model AR_XL_5 has incorrect name and does not start Missing KWS model AR_XL_5 Processing of some short recordings causes TwoGmmCalibThreshold is not finite error STT preferred phrases "out of vocabulary" (OOV) warning message is now more verbose

What are STT preferred phrases and how to use them

     Posted on: 2020-11-26

Speech Engine version 3.32 and later includes new STT feature called Preferred phrases. This article explains what is the feature good for, how does it work internally and gives some tips for practical implementation. What are preferred phrases In the speech transcription tasks, there may be situations where similar sounding words get confused, e.g. "WiFi" vs. "HiFi", "route" vs. "root", "cell" vs. "sell", etc. Normally, the language model part of the Speech To Text does its job here and in the context of longer phrase or entire sentence prefers the correct word:  ×    I'm going to cell my car. Hmmm, such…

Speech Engine 3.35.1

     Posted on: 2020-10-13

Speech Engine 3.35.1, DB v1600, BSAPI 3.35.1 (2020-10-13) Fixed Missing input stream task name in log messages Missing arguments in "word not found" error messages (when using preferred phrases)

Speech Engine 3.35.0

     Posted on: 2020-10-01

Speech Engine 3.35.0, DB v1600, BSAPI 3.35.0 (2020-10-01) New LID model L4 was promoted to production (LID BETA_L4 renamed to LID L4) Added new language tag documentation (doc/Technology_LID_L4_Language_tags.pdf) Updated STT model CS_CZ_5 to version 5.2.1 (fixes faulty transcription of numbers into Roman format) Added configurable STT Confusion Network threshold (in technology configuration file) Fixed STT didn't work with 4th and older generation models after introduction of the Preferred phrases feature in SPE 3.32 Update from SPE 3.30 causes errors in STT result cache memory leak in logging system Typo in name of es-XA language in LID model L4 default language…

Technical Training Essentials

     Posted on: 2019-09-27

Core objective: Understanding technical essentials of using Phonexia technologies and products Duration: ~94 minutes (7 + 19 + 22 + 23 + 23 min chapters) intended for product architects or developers assumes you have already watched Phonexia technologies introduction video assumes understanding of working in command line REST API principles processing JSON or XML Introduction (7 min) technologies recap CLI, REST and GUI interfaces overview MODULE 1: Getting started with Speech Engine (19 min) Installation Technologies configuration Server and database configuration Users configuration Files processing Synchronous and asynchronous requests, results polling Stream processing MODULE 2: Filtering and supporting…

Keyword Spotting

     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…

Speech To Text results explained

     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 To Text

     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…