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Speech To Text results explained

Relevance: 100%      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 several types of output to show only one or more transcription alternatives. One-best output 1-best output provides transcription containing only the highest-scoring words. Each segment provides information about the transcribed word itself, the…

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

Relevance: 92%      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

Speaker Identification: Results Enhancement

Relevance: 92%      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,…

Language Identification results explained

Relevance: 92%      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.…

Keyword Spotting results explained

Relevance: 92%      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…

Voice Inspector – Interpretation of results

Relevance: 92%      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…

Q: Please describe how to get the results for a pending operation.

Relevance: 83%      Posted on: 2017-06-27

A: If server responds on pending request by status 200 - OK,  the body of the response will have the result inside (server already has the result in cache memory and there is no need to process the file again). If server responds on pending request by status 202 - Accepted, server will create task and server will begin to process the file. In response HTTP header (in parameter "Location") there is path for pending resource. In the body there is a ID of pending operation. Polling: Client asks on the pending resource (e.g. “get /pending/{ID}). Server will answer with…

Q: Can I add words into dictionary?

Relevance: 17%      Posted on: 2017-06-27

A: It is possible to add words to the dictionary, it is service provided within support by Phonexia once per quartal for a customer. For best results customer should provide our transcription + his correction and multiple types of pronunciation for the specific word.

Voice Inspector – supporting technologies

Relevance: 17%      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)…

Phonexia Speech Engine

Relevance: 17%      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…