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Phonexia Speech Platform Release Plan

     Posted on: 2020-05-15

Starting with year 2020, Phonexia products use two types of releases: RELEASE TYPE FREQUENCY GENERAL AVAILABILITY SUPPORT Feature Max. once per month Limited (project based) Limited (project based) Public Twice a year (end of Q1 and Q3) No restrictions Standard Phonexia support Feature releases contain fresh new features, primarily intended for Proof-of-Concept projects and partners' testing of the new features in the wild and collecting feedback. Based on the feedback, the behavior of the features can be improved or changed in subsequent releases. Feature releases are created on approx. monthly basis. Feature releases are provided on a project basis, or…

How to convert STT confusion network results to one-best

     Posted on: 2020-04-06

Confusion Network output is the most detailed Speech Engine STT output as it provides multiple word alternatives for individual timeslots of processed speech signal. Therefore many applications want use it as the main source of speech transcription and perform eventual conversion to less verbose output formats internally. This article provides the recommended way to do the conversion. Time slots and word alternatives: The recommended algorithm for converting Confusion Network (CN) to One-best is as follows: loop through all CN timeslots from start to end in each timeslot, get the input alternative with highest score and if it's not <null/> or…

What is a user configuration file and how to use it

     Posted on: 2020-03-28

Advanced users with appropriate knowledge (gained e.g. by taking the Phonexia Academy Advanced Training) may want to finetune behavior of the technologies to adapt to the nature of their audio data. Modifying original BSAPI configuration files directly can be dangerous – inappropriate changes may cause unpredicatble behavior and without having a backup of the unmodified file it's difficult to restore working state. User configuration files provide a way to override processing parameters without modifying original BSAPI configuration files. WARNING: Inappropriate configuration changes may cause serious issues! Make sure you really know what you are doing. User configuration file is a…

How to configure STT realtime stream word detection parameters

     Posted on: 2020-03-28

One of the improvements implemented since Speech Engine 3.24 is neural-network based VAD, used for word- and segment detection. This article describes the segmenter configuration parameters and how they are affecting the realtime stream STT results. The default segmenter parametrs are as shown below: [vad.online_segmenter:SOnlineVoiceActivitySegmenterI] backward_extensions_length_ms=150 forward_extensions_length_ms=750 speech_threshold=0.5 Backward- and forward extension are intervals in miliseconds, which extend the part of the signal going to the decoder. Decoder is a component, which determines what a particular part of the signal contains (speech, silence, etc.). Based on that, decoder also decides whether segment has finished or not. Unlike in file processing…

How to configure Speech Engine workers

     Posted on: 2020-03-28

Worker is a working thread performing the actual files- or realtime streams processing in Speech Engine. This article helps to understand the Speech Engine workers and provides information how to configure workers for optimal performance and server utilization. The default workers configuration in settings/phxspe.properties is as shown below – 8 workers for files processing and 8 workers for realtime streams processing. These numbers mean the maximum number of simultaneously running tasks. # Multithread settings server.n_workers = 8 server.n_realtime_workers = 8 Requests for additional file processing tasks are put in a queue and processed according their order and priorities. Requests for…

Browser3 – Releases and Changelogs

     Posted on: 2020-03-27

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 v3.30.0, BSAPI 3.30.0 - Mar 27 2020 Public release Fixed: Target and non-target graphs in SID evaluator are swapped Fixed: PDF chart could be empty in the SID evaluator report Fixed: JSON parsing error during evaluation set creation when some file doesn't contain any speech Updated: Synchronize versioning with BSAPI Phonexia Browser v3.26.0, BSAPI 3.26.0 - Feb 28 2020 Non-public Feature Preview release…

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

     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…

Measuring of a software processing speed – what is the FtRT (Faster than Real Time)

     Posted on: 2019-10-30

Faster Than Real Time (FTRT) is metrics developed for defining software performance reference point. Using this metric you can collect "benchmark" data of real processing speed for reviewed software, which should be found - and reproduced - on exactly defined HW. Then, comparing various benchmarks result, you can compare performance of the specified software and its parts on different HW configurations. And vice versa - using the same metric you can compare software from different vendors on the same HW configuration and for the same processing task. We are recognizing two measurable metrics: Recording based FTRT is calculated from real…

TUTORIAL: Speaker Identification – How to Do a Basic Test

     Posted on: 2019-10-08

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…

Workflow – Releases and Changelogs

     Posted on: 2019-10-07

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. This page lists changes in Workflow releases. Changelogs == Phonexia Workflow v1 == Phonexia Workflow 1.4.1 (10/07/2019) - SPE 3.16 - 3.17 Support for IPv4 only (since SPE does not support IPv6) Configurable application webhook address in both Workflow Runner and Data Discovery Tool This address is auto-detected when no value is supplied - default In some cases like network specific configuration it might be necessary to configure it manually Rapid…

Technical Training Essentials

     Posted on: 2019-09-27

Core objective: Understanding technical essentials of using Phonexia technologies and products Duration: ~94 minutes (7 + 19 + 22 + 23 + 23 min chapters) intended for product architects or developers assumes you have already watched Phonexia technologies introduction video assumes understanding of working in command line REST API principles processing JSON or XML Introduction (7 min) technologies recap CLI, REST and GUI interfaces overview https://youtu.be/xzrHyyIl01s MODULE 1: Getting started with Speech Engine (19 min) Installation Technologies configuration Server and database configuration Users configuration Files processing Synchronous and asynchronous requests, results polling Stream processing https://youtu.be/4qrB-GfFdWY MODULE 2: Filtering and supporting…

Phonexia Workflow

     Posted on: 2019-08-06

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 filters out low quality audio files, provides demographic information, age estimation and speech to text processing VbsEssentials - Voice Biometrics Essentials filters out low quality audio files, provides gender identification, age estimation and speaker identification  The scenario is a tiny Java application which interacts with Phonexia technologies…

How do you calculate SNR in Speech Quality Estimation?

     Posted on: 2019-07-01

Signal-to-Noise Ratio (SNR) is an important metric of whether a recording is worth further processing by other speech technologies, so it is part of our Speech Quality Estimation. However, calculating SNR automatically is not a trivial task. We use the fact that the statistical distribution of the frequencies in the waveform of speech has Gamma distribution. In contrast, noise has Gaussian distribution. So we can estimate the SNR by looking at the frequency distribution in individual frames. This approach to SNR estimation is based on the article by Kim Chanwoo, and Richard M. Stern, called "Robust Signal-to-Noise Ratio Estimation Based…

Voice Inspector – supporting technologies

     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)…

Voice Inspector – Interpretation of results

     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…

Speaker Identification (SID)

     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.…

Keyword Spotting results explained

     Posted on: 2019-06-12

This article aims on giving more details about Keyword Spotting outputs and hints on how to tailor Keyword Spotting to suit best your needs. Scoring Keyword Spotting works by calculating likelihoods that at a given spot occurs a keyword or just any other speech, and comparing those two likelihoods. The following scheme shows Background model for anything before the keyword (1), the Keyword model (2) and a Background model of any speech parallel with the keyword model (3). Models 2 and 3 produce two likelihoods – Lkw and Lbg (any speech = background). Raw score is calculated as log likelihood…

Keyword Spotting

     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 Identification: Results Enhancement

     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,…

Speech To Text results explained

     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 various output types which show only single or multiple transcription alternatives. For processing realtime streams, two result modes are supported – one mode provides complete transcription, second mode provides incremental results. Output types…

Speech To Text

     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…

Language Identification (LID)

     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 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…

STT Language Model Customization tutorial

     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…

Phonexia End User License Agreement

     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.

Phonexia technologies introduction

     Posted on: 2019-01-25

Core objective: Basic understanding of Phonexia speech technologies and products; typical use cases, implementations and deployment topologies Duration: 35 minutes intended for idea makers and product designers assumes generic knowledge of Phonexia and speech technologies in general Content 00:00 Introduction What information can we get from speech? Overview of basic use cases Phonexia Speech Platform brief 4:21 Phonexia technologies overview and their usages Filtering and supporting technologies 04:32 Speech Quality Estimation (SQE) 05:27 Voice Activity Detection (VAD) 06:37 Diarization (DIAR) 07:41 Age Estimation (AGE) 08:14 Waveform Denoiser Voice Biometrics technologies 08:56 Speaker Identification (SID) 10:18 Language Identification (LID) 11:10 Gender…

Error 1007: Unsupported audio format

     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…

Supported audio formats

     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>…

Error 1013: Unsupported: Server does not support authentication with token

     Posted on: 2018-12-10

Please check SPE subdirectory ./settings for configuration files. If only phxspe.browser.properties exists, then your Browser uses SPE as embedded component and set inside the file this directive: server.enable_authentication_token = false In that case you can still use SPE with Basic HTTP authentication, as described in documentation, section "Basic authentication" If you would like to play with "pure" daemon installation, then phxspe.properties file should exist in ./settings subdirectory. File phxspe.properties is created by phxadmin utility or can be created from ./data/phxspe.properties.default template file. Copy template file to ./settings directory Rename it to phxspe.properties Check for server.enable_authentication_token directive and setup it as…

Phonexia Voice Inspector EoL

     Posted on: 2018-07-19

Information about release dates, support and maintenance periods of Phonexia Voice Inspector.

Phonexia technology models EoL

     Posted on: 2018-07-11

Information about release dates, support and maintenance periods of Phonexia technology models.

Phonexia Speech Engine EoL

     Posted on: 2018-06-19

Information about release dates, support and maintenance periods of Phonexia Speech Engine (software End of Life - EoL).

SPE3 – Quick Start Guide

     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…

Gender Identification

     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).

SPE3 – Administration and Backup

     Posted on: 2018-04-15

Each Partner has its own administration and back up policy. Here, we highlight the most important SPE3 components to be administrated and backed up. Administration It is strongly recommended to describe your own administration approach with the following components SPE users (accounts) - Partner should maintain list of SPE users (accounts). There should be only few persons with “admin” role. All other should be with “user” role (do not see content of other “user”) and/or “vbs” role (dis/enables using of VoiceBiometry plugin) the SPE database and/or VBSplugin database administration – where the (temporary) results are stored user.home - where the…

Designing and Developing Application

     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…

Packages, Updates vs. Upgrades

     Posted on: 2018-04-15

Our packages follow the bug-fix /updates / upgrades approach. Some packages are distributed with limited set of speech technologies or without speech technologies. Packages Our software is distributed as ZIP file. Installation procedure is matter of unzipping archive, reconfiguration and start of software. SPE and VIN package contains speech technologies (note: SPE might contain only selected technologies).  PhxBrowser does not contain speech technologies and it needs to be combined with SPE. The software is activated by licensing file. Updates vs. Upgrades Bugfix By bugfix we understand a fix of known problem without changing components or technology models. Bugfix changes only…

Time Analysis

     Posted on: 2018-04-15

Time Analysis Extraction (TAE) by Phonexia extracts base information from dialogue in a recording, providing essential knowledge about conversation flow. That makes it easy to identify long reaction time, crosstalk, or responses of speakers in both channels. This technology is only meaningful when used on recordings with 2 channels. As an answer to the TAE technology, SPE returns a json/xml file. This file includes general information about the technology and details of the time analysis. The technology can work either with a closed recording or with a stream. Monologue Describes the statistics of a recording related to one channel. channel…

Age Estimation

     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…

VIN – Releases and Changelogs

     Posted on: 2018-04-08

Phonexia Voice Inspector (VIN) is developed as a desktop application for forensic speaker comparison. This page lists changes in VIN releases. Releases Changelogs Voice Inspector v4.0.0, BSAPI 3.23.0 - Dec 11 2019 - VIN is available with L4 technology model - Other technology models (S2, L2, L3, XL3) are no longer supported - Added Diarization Technology (available in waveform editor) - Population Sets structure changed - Reworked dialog for population set management - Added possibility to set type of estimation of the Target distribution - Using population set to estimate Target distribution allows 1:1 comparison - Bug fixes Voice Inspector…

Voice Biometrics

     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…

Speech Analytics

     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…

Software Vetting

     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,…

Open Source Acknowledgement

     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 ADVobfuscator 1.1 link static boost 1.70 Boost License static botan 2.7.0 Simplified BSD static duktape 2.5.0 MIT static FLAC 1.3.2 BSD license static fmt 5.2.1 MIT static glibc - GNU LGPL dynamic (Linux) minizip 1.2.11 link static mkl 2019.1.144 ISSL static nowide 0.1.1 Boost License static Open Fst 1.6.9 Apache license static ogg 1.3.3 BSD license static onnxruntime 1.1.0 MIT static opus 1.2.1…

Voice Activity Detection – Essential

     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…

Speech Quality Estimator – Essential

     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…

Keyword

     Posted on: 2018-04-04

Word or a phrase that is searched by a user (defined by a user as an input for KWS technology). Phonexia does not limit the number of keywords in the keyword list. The higher number of keywords (500+) cause speed decrease.

Speaker Diarization

     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…