Voice Print – output from spoken speech extraction process of SID. Unique mathematical representation of the specific speaker. It is created from iVectors.
Search Results for: ROM
|Results 41 - 60 of 67||Page 3 of 4|
|Results per-page: 10 | 20 | 50 | 100|
Median – Value separating higher half of data sample from lower half.
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 <-∞;+∞>
Language Print Archive - pack of language prints from the recordings spoken in the same language/dialect. Used for the language identification in LID comparison.
Language Print - output data from LID technology
Features – FEA is optional output from KWS technology. Looking for keywords in FEA is faster than in original recording.
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)
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 email@example.com Registration, login to and using this website you are agree with next important Phonexia's documents: .
A: Via HTTP header “Accept” parameter (application/json; application/xml) Via request query “format=json/xml” If the format is not defined (or the HTTP header "Accept" parameter has one of these values: application/*,*/*,*), server will return json.
A: From the utilities in the package, you can find it in "ffprobe <file_name>", it will write out the info about the file. *Utility "ffprobe" is not included in our package(s). It is part of ffmpeg (https://ffmpeg.org/ffprobe.html) and it is neccessary to install it separately.
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)
A: The language-prints do not depend on the current language pack used. You may use them for both training a new language pack and testing/comparing against an existing language pack. The language-prints needs to be compatible only with the model of LID used for language-print extraction.
[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.
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
A: These abbreviations mean the following: LR - likelihood ratio, result from statistical test for two models comparison. It returns a number which expresses how many times more likely the data are under one model than the other. LR meets numbers in interval <0;+inf). LLR - abbreviation for log-likelihood ratio statistic, logarithmic function of LR. LLR meets numbers in interval (-inf;+inf). Percentage (normalised) score - commonly used mathematical transformation of the LLR to percentage. This number is better for human readability but may bring some doubts if LLR numbers are too high (typically for some non-adapted installations). Interval <0;100> (or…
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,…
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…
This page highlights advices based on the previous experience. If you have any suggestions or correction regarding the innovation of the tech support, please let us know. The Frequently asked questions and Lifetime Support Policies sections prepared for you on Partner Portal could also be of interest to you. Any errors should be tested on the latest version of the product. Please ask your Phonexia contact for a link to download the latest version. Before submitting issue/ticket... Any errors should be tested on the latest version of the product. Please ask your Phonexia contact for a link to download…
About Phonexia Voice Inspector v1 (VIN1) provides police forces and forensic experts with highly accurate speaker identification tools to be used during the investigation of criminal matters. It utilizes the power of voice biometry to automatically recognize the speaker by their voice. Main features of the VIN1 application: An automatic speaker identification tool to strengthen the results of the standard phonetic based approaches Scoring of the likelihood ratio (LR), log-likelihood ratio (LLR), and an option of a verbal presentation of the results Graphic presentation of the likelihood ratio (LR), probability density function and Tippett plot Generating detailed reports (expert opinion…