Search Results for: Audio Source Profile

Results 21 - 30 of 55 Page 3 of 6
Results per-page: 10 | 20 | 50 | 100

Phonexia Voice Inspector v3

Relevance: 9%      Posted on: 2018-04-02

About Phonexia Voice Inspector v3 (VIN3) 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 VIN3 application: Automatic speaker identification tool to strengthen results of the standard linguistics- and phonetics-based approach Scoring in Likelihood Ratio (LR) – result from a statistical test for a comparison of two hypotheses. The system returns a number from the interval <0, +∞>, which expresses how many times more likely the data are under one hypothesis than the…

Performance of the Speaker Identification 4th generation (SID4): Intel® Xeon® Platinum 8124M

Relevance: 9%      Posted on: 2019-10-30

Benchmark goals Find realistic performance using total recording length Find FTRT based exactly on net_speech (engineering sizing data) Find system performance using all physical cores Find system performance using all logical cores Infrastructure setup Intel® Xeon® Platinum 8124M is used in virtual machine with 8 physical cores reserved exclusively for this VM, Hyper Threading is enabled [16 logical cores available], 32GB RAM, 30GB SSD based storage, 1000 I/O.s-1  reserved per core Benchmark data setup Data set statistic: Number of files: 32 [300 seconds each] RAW recordings length ∑: 9600 [sec] Net speech length ∑: 4224.77 [sec] In the data set…

Knowledge Base

Relevance: 9%      Posted on: 2017-05-18

This section collects information, we see the most important or frequently discussed. Best Practices Frequently Asked Questions (FAQ) Manuals Glossary Terminology Open Source Acknowledgement  

Keyword pronunciation

Relevance: 9%      Posted on: 2018-04-04

Pronunciation of the keyword(s) is generated automatically (G2P, grapheme to phoneme)  or produced from the lexicon of known words (“lexicon”) or converted from audio (phoneme transcription). It can be edited manually for each word (Phonexia do not limit the number of pronunciations per keywords/phrases).

Speech Analytics

Relevance: 9%      Posted on: 2018-04-06

Overview Phonexia Speech Analytics allows you to understand the  content of audio without having to listen to it. The results help both commercial entities and security/defense forces for immediate precise decision and response. The technologies reveal automatically WHAT content, TOPIC and KEY PHRASES are spoken, and many other metadata.   Speech Analytics - Typical Use-Cases Speech transcription is used in various application. Knowledge of content of whole call is bringing business value to the customer, comparing to listening the audio files by analytic or supervisor. Reading the text is also faster than listening the audio. Speech Analytics output is often…

Phonexia Speech Platform for Government

Relevance: 9%      Posted on: 2017-05-18

Phonexia Voice Biometrics GOV is a special edition of Phonexia Speech Platform for Government which allows you to understand the nature of audio without having to listen to it. The product helps people to utilize the power of voice biometrics to filter audio and prevent or identify crimes. The technologies reveal automatically WHO, what GENDER, what LANGUAGE is speaking, and many other metadata. The product can be used typically for investigation support, SIGINT or other types of operations. It serves 4 main use-cases: Voice Biometrics - Speaker Search in Archive (Investigation) Voice Biometrics - Speaker Spotting Tactical Voice Biometrics -…

Speech Quality Estimator – Essential

Relevance: 9%      Posted on: 2018-04-04

Phonexia’s Speech Quality Estimator quantifies the acoustic quality of recordings. This helps the user to quickly determine whether the acoustic quality of a recording is good for processing with other speech technologies or not. As an answer for SQE, the SPE returns a json/xml file. This file includes general information about the technology and statistics of all (one or two) channels. The statistics of all channels include the numbers for many aspects of recording quality, and the overall global score. Technology The technology is language-, accent-, text-, and channel- independent Compatibility with the widest range of audio sources possible (applies…

Phonexia Workflow

Relevance: 9%      Posted on: 2019-08-06

About Phonexia Workflow is a set of tools complementing Phonexia Speech Engine (SPE), which allow users to chain speech technologies into scenarios and process audio recordings automatically using these scenarios. Scenarios are programmed using uniform API which provides an abstraction over Phonexia Speech Engine application. Provided Phonexia Workflow scenarios: SalEssentials - Speech Analytics Essentials filter out low quality audio files, provides demographic information, age estimation and speech to text processing VbsEssentials - Voice Biometrics Essentials filter out low quality audio files, provides gender identification, age estimation and speaker identification   The scenario is a tiny Java application which interacts with…

Phonexia Speech Engine

Relevance: 9%      Posted on: 2017-05-18

About Phonexia Speech Engine v3 (SPE3) is a main executive part of the Phonexia Speech Platform. It is a server application with REST API interface through which you can access all available speech technologies. Both, Linux 64bit and Windows 64bit operating systems are supported. Phonexia Speech Engine (SPE3) is adjustable server component which houses all speech technologies. SPE3 provides RESTfull application programming interface to access various technologies. Aside from technologies themselves the SPE has implemented other various functionality supporting work with speech technologies, recordings and streams, and others. Features Main purpose of SPE is to work as processing unit for…

Voice Activity Detection – Essential

Relevance: 9%      Posted on: 2018-04-04

Phonexia Voice Activity Detection (VAD) identifies parts of audio recordings with speech content vs. nonspeech content. 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 Output Log file with processed information (speech vs. nonspeech segments) Segmentation The section Segmentation describes the results of VAD, which are segments of detected voice and silence. Segments are…