Search Results for: language model customization

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STT Language Model Customization tutorial

Relevance: 100%      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…

Language Identification (LID)

Relevance: 36%      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…

Q: How can I add new language to LID?

Relevance: 33%      Posted on: 2017-06-27

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

Language Identification results explained

Relevance: 33%      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.…

Speech To Text

Relevance: 9%      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…

Speech To Text results explained

Relevance: 6%      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 several types of output to show only one or more transcription alternatives. One-best output 1-best output provides transcription containing only the highest-scoring words. Each segment provides information about the transcribed word itself, the…

Phonexia Speech Platform

Relevance: 6%      Posted on: 2017-05-18

  Phonexia Speech Platform (Speech Platform) provides partners a complete portfolio of speech technologies with an easy-to-use design. The platform allows users to design and deploy a wide range of speech processing systems in a short time and without extensive knowledge of the technologies background. Products On top of Speech Platform, several products provided: for commercial market Phonexia Speech Analytics Phonexia Voice Biometrics for government market Phonexia Speech Analytics GOV Phonexia Voice Biometrics GOV Characteristics Completeness – all speech technologies in one place Simple to use – RESTfull API for rapid development Modularity – build your own specific process workflow…

SPE3 – Quick Start Guide

Relevance: 6%      Posted on: 2018-04-16

Do you want to run the SPE3 for the first time? This post can help you. Distribution, installation and configuration SPE is distributed by Phonexia in .zip archives. These are downloaded from Phonexia package manager using link provided by Phonexia employee. Installation is done by simple unzipping the content of the downloaded .zip archive to SPE installation folder. Configuration of SPE is done at two places. First is executable file ./phxadmin or .\phxadmin.exe serving to set file to configuration and license files configure speech technologies configure user accounts set up of few various setting Running the ./phxadmin or .\phxadmin.exe command…

Speaker Diarization

Relevance: 6%      Posted on: 2018-04-02

Speaker Diarization labels segments of the same voice(s) in one mono channel audio record based by the individual speaker´s voice. It is a language-, domain- and channel-independent technology. It performs not only the segmentation of speakers, but of technical signals and silence as well. The outputs of the technology can be both log file with labels and/or split audio files/one new multichannel audio file. The correct speaker diarization is still research task nowadays. Typical use cases: Preprocessing for other speech recognition technologies, labeling the parts of the utterance according to the speakers, splitting telephone conversation recorded in mono into several…

Voice Inspector – supporting technologies

Relevance: 6%      Posted on: 2019-06-28

Automatic Speaker Identification (SID) is the most important but not the only Phonexia technology that is implemented in Voice Inspector (VIN). Apart from SID, forensic experts, users of VIN, can benefit from automatic Signal-to-Noise Ratio calculation, Voice Activity detection, Phoneme search, and a Wave editor which incorporates the waveform, spectrum and power panel. Let's have a look on how to utilize individual technologies. Signal-to-Noise Ratio Recording quality can strongly influence the reliability of SID results and so the outcome of a forensic case. Therefore, VIN uses a module of Phonexia Speech Quality Estimation (SQE) to calculate the Signal-to-Noise Ratio (SNR)…

SPE configuration

Relevance: 6%      Posted on: 2018-02-02

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

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

Relevance: 6%      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)

Speech Intelligence Resolver v1

Relevance: 6%      Posted on: 2017-05-18

About Phonexia Speech Intelligence Resolver v1 (SIR1) combines the power of speech technologies within a single application. The application automatically performs visualization of the record as well as filtering the speech metadata uncovered from your records effectively. Speech technologies implemented: Phonexia Speaker Identification (SID2) Phonexia Language Identification (LID2) Phonexia Gender identification (GID) Phonexia Voice Activity Detection (VAD) Phonexia Speaker Diarization (DIAR) Phonexia Keyword Spotting (KWS) Phonexia Speech Quality Estimator (SQE) Phonexia Speech Transcription (STT) SIR is a client application cooperating with REST servers. It can be used as a standalone application due to the integrated local REST server. It was…

Voice Biometrics Course (technical training)

Relevance: 6%      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…

Browser3 – Releases and Changelogs

Relevance: 6%      Posted on: 2019-10-09

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 v3.18.0, BSAPI 3.22.0 - Oct 03 2019 New: Waveform editor can now process stereo file by Diarization in per-channel mode New: Added Gender balance and Score sharpness in Settings -> Scoring New: Multiple columns in Result pane can be turned on/off at once using context menu New: Minimum speech length changed to 7 seconds Fixed: LID results information chart is not updated…

Speaker Identification: Results Enhancement

Relevance: 6%      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,…

Speaker Identification (SID)

Relevance: 6%      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.…

Speech Analytics Course (technical training)

Relevance: 6%      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…

Gender Identification

Relevance: 6%      Posted on: 2018-04-16

Gender Identification is a language-, domain- and channel-independent technology that uses the acoustic characteristics of the recording to determine the gender of the speaker in question. This technology is able to distinguish between two genders: Male (M) and Female (F). Minimum of speech signal for identification: 9+ sec recommended Output scoring: likelihood ratio and percentage metric (0-100%) Typical use cases: filtering calls by gender, playing advertisement focused on specific gender, getting quick demographic analysis of the recordings. The speed of Gender Identification is up to 150 FtRT (depending on the model).