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And filters to play around with and other excellent tools that you can use to jazz up your photos before posting them. If you’re looking for an easy way to share moments with your friends, try the video option and capture them that happen instantly.Check out its following parameters:Domain Authority (DA) – 92Launched In – 2011Monthly Active Users (MAU) – 265 MillionHeadquarters – Santa Monica, California, United States VK - A Russian Social Sharing Site VK is a top social sharing platform in Russia, and it is one of the largest in Europe having in excess of 100 million active users.It contains qualities not found in other social networks such as personalized news feed algorithms and video streaming. They have a more European focus, so it’s a must-have if you’re looking for a social sharing site geared toward Europeans and reach out to people from Eastern Europe or Central Asia.VK is mainly made up of the older generations, so it’s not an ideal place for those hoping to market themselves in the US or other countries worldwide.It is used mainly in Eastern Europe and Central Asia and is not popular in North America because they feel that Facebook or Instagram are better options.Check out its following parameters:Domain Authority (DA) – 96Launched In – 2006Monthly Active Users (MAU) – 649 MillionHeadquarters – Moscow, Russia Minds Social Network Minds is a blockchain-based social network that has received less attention than others but is worth checking out.You can get an option of earning money by using Minds.The platform is similar to Steemit, a popular Reddit-like social media website that rewards users for good content.It offers a more intimate experience where you can get the personal attention and feedback of the people in your network. Users of Minds can send messages or private chats

Faster than real-time! Based on Mozilla’s DeepSpeech Engine 0.9.* June 2020: Revised instructions for DeepSpeech version 0.7.*, except Raspberry Pi 4 screenshots which remained unchanged. The benchmark table has remained the same, as I didn’t observe any improvement in inference speed. However, there appears to have been a precision enhancement – the audio file 2830-3980-0043.wav, previously transcribed as “experience proofless”, is now transcribed as “experience proves this”, making it more coherent. The article can still be accessed on Steemit in its archived form. I recently added a hot word script to mic_streamIn this article we’re going to run and benchmark Mozilla’s DeepSpeech ASR (automatic speech recognition) engine on different platforms, such as Raspberry Pi 4(1 GB), Nvidia Jetson Nano, Windows PC and Linux PC.2019, last year, was the year when Edge AI became mainstream. Multiple companies have released boards and chips for fast inference on the edge and a plethora of optimization frameworks and models have appeared. Up to date, in my articles and videos I mostly focused my attention on the use of machine learning for computer vision, but I was always interested in running deep learning based ASR project on an embedded device. The problem until recently was the lack of simple, fast and accurate engine for that task. When I was researching this topic about a year ago, the few choices for when you had to run ASR (not just hot-word detection, but large vocabulary transcription) on, say, Raspberry Pi 3 were:CMUSphinxKaldiJasperLinks:Python 3 Artificial Intelligence: Offline STT and TTSThe Best Voice Recognition Software for Raspberry PiAnd a few more. Setting up any of them was not simple and they were not ideal for use in environments with limited resources. A couple of weeks ago, I revisited this topic and discovered Mozilla’s DeepSpeech engine through some investigation. It

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