Search Results for: Audio Source Profile

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Error 1007: Unsupported audio format

Relevance: 100%      Posted on: 2018-12-10

Phonexia Browser application may return error "1007: Unsupported audio format" during uploading audio file. Please consider if your audio files are in . But if you need use as input audio recordings in other formats, you can configure SPE for audio automated conversion. As prerequisite install external tool for audio conversion. Recommend is ffmpeg utility, powerful and well documented. Please find your distribution package at http://ffmpeg.org Then continue as described below: Using Phonexia Browser with embed SPE Open the Browser configuration dialog by click on button "Settings" located in tool ribbon. Select tab "Speech Engine" and configure SPE as described…

Open Source Acknowledgement

Relevance: 100%      Posted on: 2018-04-06

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. BSAPI 3 dependencies Name Version License Link type antrl 3c-3.4 BSD license static boost 1.55 Boost License static botan 1.10.9 Simplified BSD static FLAC 1.2.1 BSD license static Open Fst 1.3.4 Apache license static OpenGrm NGram 1.1.0 Apache license static ogg 1.3.2 BSD license static opus 1.1 New BSD License static libogg 1.3.2 BSD license static speex 1.2rc1 BSD license static stdlibc++, libgcc - GNU GPL with GCC Runtime Library Exception…

Supported audio formats

Relevance: 100%      Posted on: 2018-12-10

Supported audio format are: WAVE (*.wav) container including any of: unsigned 8-bit PCM (u8) unsigned 16-bit PCM (u16le) IEEE float 32-bit (f32le) A-law (alaw) µ-law (mulaw) ADPCM FLAC codec inside FLAC (*.flac) container OPUS codec inside OGG (*.opus) container   Other audio formats must be converted using external tools. SPE server can be configured to support automated conversion on background, see SPE configuration hints. Great tools for converting other than supported formats to supported are ffmpeg (http://www.ffmpeg.org) or SoX (http://sox.sourceforge.net/). Both are multiplatform software tools for MS Windows, Linux and Apple OS X. Example of usage: ffmpeg ffmpeg -i <source_audio_file_name>…

Speaker Identification: Results Enhancement

Relevance: 27%      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,…

Browser3 – Releases and Changelogs

Relevance: 27%      Posted on: 2019-07-03

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 v3.17.0, BSAPI 3.21.0 - Jul 01 2019 [G#106] Added possibility to activate/deactivate created filter rules [G#125] Running Browser in "embedded SPE" mode now creates SPE log file (phxspe.browser.log located in SPE log directory) Phonexia Browser v3.16.1, BSAPI 3.20.1 - May 17 2019 [G#112] Fixed Denoiser which created duplicate recordings under specific circumstances [G#127] Fixed comparison of SID Evaluation sets using Audio Source

SPE3 – Releases and Changelogs

Relevance: 27%      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…

Speech To Text

Relevance: 18%      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…

Q: I found the following error: ApplicationStartup: Unhandled exception: BsapiException. What does it mean?

Relevance: 18%      Posted on: 2017-06-27

[Error] ApplicationStartup: Unhandled exception: BsapiException: SWaveformSegmenterI(/mnt/phxspe/home/phx/storage/dfs/a1cabcf7-c761-49f1 -a9bc-0a8209a09fd9.opus Requested segment (78056, 102056) is out of waveform range (0,91840). Any ideas what this means? A: It means that this opus file is created improperly and declares internally (in header) much more audio than available in real file. Please check your audio source/originator for proper functionality. Or use ffmpeg / sox utility as preprocessor of the audio and do audio normalization by self-conversion from opus to opus before recordings are processed through SPE.

Speaker Identification (SID)

Relevance: 18%      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.…

STT Language Model Customization tutorial

Relevance: 18%      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 results explained

Relevance: 18%      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.…

SPE configuration

Relevance: 18%      Posted on: 2018-02-02

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

Voice Inspector – Interpretation of results

Relevance: 18%      Posted on: 2019-06-24

Introduction Phonexia Voice Inspector (VIN) is a tool for forensic automatic speaker identification, compliant with the Methodological Guidelines for Best Practice in Forensic Semiautomatic and Automatic Speaker Recognition, published by the European Network of Forensic Science Institutes.  This post explains individual SID score types and ways to visualize the results in a speaker identification case implemented in Voice Inspector. Evidence In VIN, the term evidence has two meanings. In general, it refers to any SID score that the system calculates for any pair of recordings in the case. These scores are the output of the Phonexia SID technology which runs…

Product Portfolio

Relevance: 18%      Posted on: 2018-04-02

Phonexia Speech Platform is an umbrella concept for all Phonexia’s products and services related to speech technologies. It gives us the ability to customize various products to a wide range of customer needs. Platform Edition is an encapsulation of specific setup of speech technologies, modules, applications, utilities and services designed for a specific market segment. We distinguish Speech Analytics (SAL) and Voice Biometrics (VBS) as most common domain of usage. It is also a tool for marketing and sales. Voice Biometrics is focused more on identifying speaker, gender, language spoken and more. Speech Analytics focuses on gathering information about content…

Voice Biometrics

Relevance: 9%      Posted on: 2018-04-07

Overview Phonexia Voice Biometrics is a special edition of Phonexia Speech Platform 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 verify speaker or identify crimes. The technologies reveals automatically WHO, what GENDER, what LANGUAGE is speaking, and many other metadata. Voice Biometrics - Typical Use-Cases Use case Speaker Verification is tailored to banks/insurance companies/money lending companies and others, where is needed to confirm if caller/voice in audio file is the same person who is known to the customer. For this use…

Phonexia Speech Platform

Relevance: 9%      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…

Q: While trying to install SPE3, I get the error for loading libasound.so.2 libraries.

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

Currently I’m trying to install the provided binaries for Linux, but I do get the following when running phxadmin: ./phxadmin: error while loading shared libraries: libasound.so.2: cannot open shared object file: No such file or directory I’m trying to run this under CentOS 7. A: Please install sound libraries required for manipulation with audio files from official repository into your OS. For CentOS you may use: sudo yum install alsa-utils alsa-lib Hint: Great utility for finding subsequent Redhat/Fedora/CentOS libraries is https://www.rpmfind.net/linux/RPM/index.html

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…

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 combines Phonexia technologies into scenarios, which can be easily configured and deployed. Phonexia Workflow uses Phonexia Speech Engine internally. 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. Our team can help you implementing your custom scenario. The scenario is a tiny Java application which interacts with Phonexia technologies and optionally can use your service or database. First steps Installation Go through…

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…

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)

Phonexia End User License Agreement

Relevance: 9%      Posted on: 2019-02-27

Please read the terms and conditions of this End User License Agreement (the “Agreement”) carefully before you use the Phonexia proprietary software providing speech solutions, technologies and accompanying services (the “Software”) delivered and marketed by Phonexia s.r.o.

Account

Relevance: 9%      Posted on: 2018-03-21

Registered info: GDPR tools: Full name: Login name: E-mail: Change profile Change password Phonexia Partner Portal documents access level: Hints: General rules Registration for Phonexia Partner Portal is for free. But various user access levels are applied to the articles, some of them are available only for Phonexia Partners and Certified members. You may ask for promoting your access level by asking for business support on info@phonexia.com Legal documents By registration, login to and using this website you agree with the Privacy Policy and Terms of Service. .

Keyword Spotting (KWS)

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

About KWS Phonexia Keyword Spotting (KWS) identifies occurrences of key-words and/or key-phrases in audio recordings. Application areas: Security/defense Maintain fast reaction times by routing calls with specific content to human operators Search for specific information in large call archives Trigger alarms immediately (online) when an event occurs Call centers Increase operator and supervisor efficiency by searching calls Identify inappropriate expressions from operators Check marketing campaigns with automatic script compliance control Mass media and web search servers Index and search multimedia by keyword Route multimedia files and streams according to their content   KWS technology Acoustic based technology robust even with…

Difference between on-the-fly and off-line type of transcription (STT)

Relevance: 9%      Posted on: 2017-12-11

Similarly as human, the ASR (STT) engine is doing the adaptation to an acoustic channel, environment and speaker. Also the ASR (STT) engine is learning more information about the content during time, that is used to improve recognition. The dictate engine, also known as on-the-fly transciption, does not look to the future and has information about just a few seconds of speech at the beginning of recordings. As the output is requested immediately during processing of the audio, recording engine can't predict what will come in next seconds of the speech. When access to the whole recording is granted during off-line transcription…

Privacy Policy

Relevance: 9%      Posted on: 2018-03-24

Phonexia s.r.o. with registered seat at Chaloupkova 3002/1a, 612 00 Brno, Czech Republic, is a developer and provider of speech technologies software products and related services. We appreciate your visit on our websites and we are pleased that you are interested in our software products and related services. We conform our data use to the European Union’s (“EU”) General Data Protection Regulation (“GDPR”). This Privacy Policy should help you to understand how we as a data controller gather, use and protect your personal information. 1. COLLECTING PERSONAL INFORMATION When you sign up for a Phonexia Account to allow you using…

Voice Inspector

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

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 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…

Software Vetting

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

The purpose of this document is to help client to satisfy their high security standards during integration of Phonexia software to their critical infrastructure. The vetting ensures that Phonexia software is not dangerous to the client’s infrastructure in any way. It means there are no backdoors, viruses, worms, Trojan horses, spyware, adware, critical bugs, unwanted functionality, no information is sent outside the client’s infrastructure. Vetting context Speech technology is a very dynamic area with a very fast development. For example the speaker identification error rate decreases to half between each two evaluations organized by National Institute of Standards and Technology,…

Broadcasting

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

Distribution of audio and video content to a dispersed audience via any audio or visual mass communications medium, but usually one using electromagnetic radiation (radio waves)

Terms of Service

Relevance: 9%      Posted on: 2018-03-24

Description of the Services provided by Phonexia s.r.o. 1. Acceptance of Terms of Service (Terms as a Contract) 1.1. PHONEXIA-User Relationship. These Terms of Service (hereinafter referred to as "Agreement" or „Terms of Service“) and the PHONEXIA Privacy Policy govern the relationship between Phonexia s.r.o. (ID No.: 27680258, VAT No.: CZ27680258, registred seat at: Chaloupkova 3002/1a, 61200 Brno, registred by the County Court in Brno under file C, insert 5124), provider of the PHONEXIA technology (hereinafter referred to as "PHONEXIA") and you ("you", "your", „user“ or "Member"), and your use of and access to the website, PHONEXIA services or any…

Speech Intelligence Resolver v1

Relevance: 9%      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…

FtRT

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

Faster than the Real Time – processing speed on 1 instance of the speech technology. Can be described also as "X min of audio archive to be processed in Y min of the real time".

Speech Quality Estimation

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

Speech Quality Estimation is a language-, domain- and channel-independent technology that serves to quantify the quality of an audio recording. 2 most important statistics that it bases its score on are SNR (Speech-to-noise ratio) and bitrate of the recording. SQE is usually part of rapid filtration process in deployment. SQE also measures over 20 other properties of the recording, all of which can be found in the output file and further processed. See description in SPE documentation. Typical use cases are: verification of recordings' quality on the input, searching based on quality of the recording, noise of environment or speaker's…

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…

Age Estimation

Relevance: 9%      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…

Voice Activity Detection

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

Voice Activity Detection is a language-, domain- and channel-independent technology that identifies parts of audio recordings with speech content vs. non-speech content. It creates labels for speech and other signals in the recording; this can then serve as a decision point whether to process the recording by other technologies or not. VAD is usually part of rapid filtration process in deployment. Typical use cases are: detection of present or absent human speech for voice processing, filtering non-speech parts of the recording, filtering out recordings with not enough net speech to be processed by other technologies voice activated process, etc. The…

Software Vetting (Best Practice)

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

The purpose of this document is to help client to satisfy their high security standards during integration of Phonexia software to their critical infrastructure. The vetting ensures that Phonexia software is not dangerous to the client’s infrastructure in any way. It means there are no backdoors, viruses, worms, Trojan horses, spyware, adware, critical bugs, unwanted functionality, no information is sent outside the client’s infrastructure. Vetting context Speech technology is a very dynamic area with a very fast development. For example the speaker identification error rate decreases to half between each two evaluations organized by National Institute of Standards and Technology,…

Licensing (technical details)

Relevance: 9%      Posted on: 2018-03-02

This document describes all licensing types for Phonexia product licensing available to our partners and customers. Each partner/customer can choose the licensing variant which best fits the current project or infrastructure. The document does not describe business conditions of Phonexia licensing. What is the License? The License is a formal agreement regarding “The Product Usage Rights” between Phonexia s.r.o. and a user of any Phonexia technology or Phonexia product. Licenses are issued by the Business Department for all speech technologies and products, and may be required in order to use utilities and tools developed by Phonexia or partners. For technical…

Voice Inspector – supporting technologies

Relevance: 9%      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)…

Speaker Diarization

Relevance: 9%      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…

Language Identification (LID)

Relevance: 9%      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…

Designing and Developing Application

Relevance: 9%      Posted on: 2018-04-15

Before designing and developing the application, we encourage Partner to find clear answer for the following questions: Customer requirements: Do my customers need file processing (audio) or stream processing in real time? What is the human power of the customer that can analyze the results? How many minutes per day or streams in parallel do my customer need to process? What are real benefits for customer (finding the needle in haystack, approaching new information, processing only few data with highest possible accuracy)? How the solution match the current processes and infrastructure of the customer? How many false alarms are acceptable…

Keyword Spotting

Relevance: 9%      Posted on: 2019-06-03

Phonexia Keyword Spotting (KWS) identifies occurrences of keywords and/or keyphrases in audio recordings. It can help you to get valuable information from huge quantities of speech recordings. You only need to specify the keywords or phrases you wish to find. This technology identifies all recordings with keyword occurrences and allows you to automatically route important recordings or calls to your experts. Typical use cases Call centers increase operator and supervisor efficiency by searching calls identify inappropriate expressions from operators check marketing campaigns with automatic script-compliance control Mass media and web search servers index and search multimedia by keyword route multimedia…

Speaker Diarization (DIAR)

Relevance: 9%      Posted on: 2017-06-26

About DIAR Phonexia Speaker Diarization (DIAR) enables segmentation of voices in one monochannel audio record. 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 (segmentation of speech, silence, and technical signals – ie. elimination of phone lines beeps, DTMF tones, music, pauses, etc.) Audio file extracted for each…