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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…

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…

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…