Search Results for: language pack

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Language Identification (LID)

Relevance: 55%      Posted on: 2019-05-20

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 any text, language, dialect, or 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…

Language Identification results explained

Relevance: 55%      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.…

Q: How can I add new language to LID?

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

A: There are multiple methods to train a new language, please see article in Components > Speech Technologies > LID.

STT Language Model Customization tutorial

Relevance: 50%      Posted on: 2019-04-24

Language Model Customization tool (LMC) provides a way to improve the Speech To Text performance by creating customized language model. Language model is an important part of Phonexia Speech To Text. In a simplified way it can be imagined as a large dictionary with multiple statistics. The Speech To Text technology uses this dictionary and statistical model to convert audio signals into the proper text equivalents. Due to general diversity of spoken speech, the default generic language model may not acknowledge the importance of certain words over other words in certain situations. Language model customization is a way to inform the…

Q: Please give me a recommendation for LID adaptation set.

Relevance: 9%      Posted on: 2017-06-27

A: The following is recommended: For adding new language to language pack 20+ hours of audio for each new language model (or 25+ hours of audio containing 80% of speech) Only 1 language per record For adapting the existing language model (discriminative training) 10+ hours of audio for each language May be done on customer site. May be done in Phonexia using anonymized data (= language-prints extracted from a .wav audio)

SPE3 – Releases and Changelogs

Relevance: 9%      Posted on: 2019-08-22

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 == SPE v3.17.x == Speech Engine 3.17.3 (08/22/2019) - DB v1200, BSAPI 3.21.3 [G_#191] Fixed: KWS getting phonemes/graphemes in specific circumstances returns unknown error [G_BSAPI#413] Fixed: duplicated output from KWS Speech Engine 3.17.2 (08/02/2019) - DB v1200, BSAPI 3.21.2 [G_BSAPI#300] Fixed: KWS stream results are displayed with a delay Speech Engine 3.17.1 (07/22/2019) - DB v1200, BSAPI 3.21.1 Added 5th generation of…

Terminology

Relevance: 9%      Posted on: 2017-06-15

Document which briefly describes processes and relations in Phonexia Technologies with consideration on correct word usage.   SID - Speaker Identification Technology (about SID technology) which recognize the speaker in the audio based on the input data (usually database of voiceprints). XL3, L3,L2,S2 - Technology models of SID. Speaker enrollment - Process, where the speaker model is created (usually new record in the voiceprint database). Speaker model: 1/ should reach recommended minimums (net speech, audio quality), 2/ should be made with more net speech and thus be more robust. The test recordings (payload) are then compared to the model (see…

LPA

Relevance: 9%      Posted on: 2018-02-01

Language Print Archive - pack of language prints from the recordings spoken in the same language/dialect. Used for the language identification in LID comparison.

SPE configuration

Relevance: 5%      Posted on: 2018-02-02

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