Search Results for: speed

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Measuring of a software processing speed – what is the FtRT (Faster than Real Time)

Relevance: 100%      Posted on: 2019-10-30

Faster Than Real Time (FTRT) is metrics developed for defining software performance reference point. Using this metric you can collect "benchmark" data of real processing speed for reviewed software, which should be found - and reproduced - on exactly defined HW. Then, comparing various benchmarks result, you can compare performance of the specified software and its parts on different HW configurations. And vice versa - using the same metric you can compare software from different vendors on the same HW configuration and for the same processing task. We are recognizing two measurable metrics: Recording based FTRT is calculated from real…

SPE3 – Releases and Changelogs

Relevance: 15%      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:…

SPE configuration

Relevance: 12%      Posted on: 2018-02-02

Basic explanation of configuration directives for SPE with hints & tips. Overview of phxspe.properties for beginners.

Language Identification (LID)

Relevance: 8%      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…

How to configure Speech Engine workers

Relevance: 8%      Posted on: 2020-03-28

Worker is a working thread performing the actual files- or realtime streams processing in Speech Engine. This article helps to understand the Speech Engine workers and provides information how to configure workers for optimal performance and server utilization. The default workers configuration in settings/phxspe.properties is as shown below – 8 workers for files processing and 8 workers for realtime streams processing. These numbers mean the maximum number of simultaneously running tasks. # Multithread settings server.n_workers = 8 server.n_realtime_workers = 8 Requests for additional file processing tasks are put in a queue and processed according their order and priorities. Requests for…

Age Estimation

Relevance: 4%      Posted on: 2018-04-12

Phonexia Age Estimation (AGE) estimates the age of a speaker from audio recording. The process of voiceprint extraction is similar to the extraction of SID, but as a result different features get extracted; therefore, the voiceprints extracted from AGE and SID are not mutually compatible. Technology Trained with emphasis on spontaneous telephony conversation The technology is language-, accent-, text-, and channel- independent Compatibility with the widest range of audio sources possible (applies channel compensation techniques): GSM/CDMA, 3G, VoIP, landlines, etc. Input Input format for processing: WAV or RAW (8 or 16 bits linear coding), A-law or Mu-law, PCM, 8kHz+ sampling…

Sizing of the computing units for speech technologies

Relevance: 4%      Posted on: 2018-02-02

Best practices for good sizing of Phonexia technologies depend on a few facts: Intense work with large data sets requires good performance and bandwidth between RAM and CPU. It all depends on the size of the files with technological models data, usually loaded into RAM and used intensively for computing operations Always think only about physical cores of CPU (HT, VT features can't help in performance) Also seek for CPUs with a large L3 cache. And the better CPUs are those with higher l3_cache_size/#_of_physical_CPU_cores ratio. We currently assume that CPUs from the current Intel Xeon Family in the 4th generation…

Time Analysis

Relevance: 4%      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…

Speaker Identification (SID)

Relevance: 4%      Posted on: 2019-06-13

Phonexia Speaker Identification uses the power of voice biometry to recognize speakers by their voice... i.e. to decide whether the voice in two recordings belongs to the same person or two different people. High accuracy of Speaker Identification, the Phonexia's flagship technology, has been validated in a NIST Speaker Recognition Evaluations. Basic use cases and application areas The technology can be used for various speaker recognition tasks. One basic distinction is based on the kind of question we want to answer. Speaker Identification is the case when we are asking "Whose voice is this?", such as in fake emergency calls.…

Speaker Identification: Results Enhancement

Relevance: 4%      Posted on: 2019-05-29

Speaker Identification (SID) Results Enhancement is a process that adjusts the score threshold for detecting/rejecting speakers by removing the effect of speech length and audio quality. This is achieved by use of Audio Source Profiles, that represent as closely as possible the source of the speech recording (device, acoustic channel, distance from microphone, language, gender, etc.). Although the out-of-the-box system is robust in such factors, several result enhancement procedures can provide even better results and stronger evidence. Audio Source Profile An Audio Source Profile is a representation of the speech source, e.g., device, acoustic channel, distance from microphone, language, gender,…