Phonexia Speaker Identification is a voice biometry tool for recognition of speakers by their voice. In this video, we will show you how to start using this technology! You will learn how to create a "Speaker Model" to identify a speaker in a set of data. Ready to test it? Start with our video: What else is needed? 1. Phonexia Evaluation Package Evaluation package (download page) is consisting of Phonexia Browser and Phonexia Speech Engine including all necessary technologies. 2. Data We prepared the dataset for your testing. Package contains data for speaker model creation and speaker spotting too. The…
We can prepare a testing package for you, basic duration 90 days, full functionality, NET license based (needs the Internet connection to register itself on the server).
This page collect information about Open Source code and licenses. You might be interested to ask your Phonexia contact what part of the page is relevant to your project. Phonexia Voice Verify dependencies Name Version License Django 2.1.11 BSD Jinja2 2.11.2 BSD-3-Clause MarkupSafe 1.1.1 BSD-3-Clause Pygments 2.6.1 BSD License beautifulsoup4 4.9.1 MIT behave 1.2.6 BSD behave-django 1.4.0 MIT certifi 2020.6.20 MPL-2.0 chardet 3.0.4 LGPL coreapi 2.3.3 BSD coreschema 0.0.4 BSD defusedxml 0.6.0 PSFL django-allauth 0.39.1 MIT django-constance 2.7.0 BSD django-cors-headers 3.4.0 MIT License django-environ 0.4.5 MIT django-extra-fields 2.0.5 Apache-2.0 django-picklefield 3.0.1 MIT django-rest-auth 0.9.3 MIT djangorestframework 3.9.1 BSD docker 4.2.2 …
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 v3.35.2, BSAPI 3.35.2 - Oct 21 2020 Public release Fixed: Speaker identification dialog in WaveEditor which did not work for SID4 Fixed detection of certain USB license tokens Phonexia Browser v3.35.0, BSAPI 3.35.0 - Oct 02 2020 Public release New: Compatibility with SPE 3.35 Phonexia Browser v3.30.12, BSAPI 3.30.11 - Aug 20 2020 Public release Fixed: Transcription results intermittently displays words in wrong…
About Phonexia Voice Inspector (VIN) provides police forces and forensic experts with a highly accurate speaker identification tool during investigation of criminal matters. It uses the power of voice biometry to automatically recognize speakers by their voice. Main features of the VIN application: Automatic speaker identification tool to strengthen results of the standard phonetics-based approaches Scoring in likelihood ratio (LR) – Result from statistical test for two models comparison. It gives back number which expresses how many times more likely the data are under one model than the other. LnLR or LogLR meets numbers in interval <-∞;+∞>...), and verbal presentation…
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…
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,…
Phonexia Partner Program for Government Partners This partnership program rewards partners in the government sector for selling and integrating the Phonexia’s speech recognition and voice biometrics product portfolio. Program Enrollment If you aspire to becoming a Phonexia partner, you can enroll into the Phonexia Partner Program and complete a three-month onboarding period. During this period, you will enjoy the same partnership benefits as our Silver partners. Your assigned Phonexia Account Manager will take you through all necessary legal documents, highlight every business aspect of our cooperation, and organize two calls with a pre-sales person to ensure that you understand the…
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…
Likelihood Ratio – Result from statistical test for two models comparation. It gives back number which expresses how many times more likely the data are under one model than the other. LR meets numbers in interval <-∞;+∞>
