ROXANNE
https://www.roxanne-euproject.org
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No publisherImageWeb based Training (WbT) for the engagement of technology providers and LEAs through EU Funded Projects
https://www.roxanne-euproject.org/news/blog/web-based-training-wbt-for-the-engagement-of-technology-providers-and-leas-through-eu-funded-projects
A combination of “synchronous” and “asynchronous” modes can be adopted for WbT instructions. This blog discusses various possibilities around the same.No publisher2020/04/06 08:00:50 GMT+1BlogVoiceprints and their properties
https://www.roxanne-euproject.org/news/voiceprints-and-their-properties
Speaker recognition is a technology that uses computer algorithms to analyze speech patterns and determine the identity of the speaker in a recording. Speaker recognition is an important part of the ROXANNE platform because the identities of speakers in recordings from criminal investigations are usually not known. In state of the art speaker recognition systems, recordings of variable durations are converted to fixed sized vectors [1,2,3], often referred to as voiceprints or speaker embeddings. Given such voiceprints from two recordings, their similarity can be measured to estimate how likely it is that the speaker in both the recordings is the same person. In this post we explain how voiceprints are extracted from audio. We also discuss some of their properties and what information they contain.No publisher2022/04/29 10:06:48 GMT+1Blogvoice signals.png
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No publisherImageVocabulary and Language Model Adaptation for Automatic Speech Recognition
https://www.roxanne-euproject.org/news/vocabulary-and-language-model-adaptation-for-automatic-speech-recognition
An automatic speech recognition (ASR) system is typically a statistical system using a fixed vocabulary. This means that a word which doesn’t exist in the system’s vocabulary can never be recognized correctly. These words are referred to as out-of-vocabulary words (OOV) and form a major source of errors for ASR. In order to keep the ASR system up-to-date and to decrease the OOV errors, the vocabulary and the language model must be adapted on a regular basis. The language model adaptation component, which will soon be part of the ROXANNE solution, tackles this problem by giving the end-users the opportunity to introduce new words into the vocabulary and to build custom models in a semi-automatic way.No publisher2021/12/21 08:30:19 GMT+1Blogusaar_logo.jpg
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