EngiSphere’s Post

The Hidden Math Powering Your Playlists 🎧 Ever wonder how your favorite songs come to life with such crystal-clear audio? 🤔 It's not magic, it's math! 🧮 Digital audio relies heavily on mathematical concepts like Fourier transforms and discrete-time signals to convert sound waves into digital information we can store and play back. 🎶 These principles allow us to manipulate audio in countless ways, from applying cool effects to compressing files for easy sharing. Want to dive deeper into the fascinating world of digital audio and its mathematical foundations? Check out my site enochchan01.com for more insights. #DigitalAudio #Mathematics #SignalProcessing #SoundEngineering #TechTalk

Exploring the World of Audio Features with Librosa – Part 3: Spectrograms In the latest installment of my blog series, I dive deep into the fascinating world of spectrograms—a powerful tool for visualizing audio signals in both the time and frequency domains. 🎶 Why spectrograms? While Fourier Transforms are excellent for analyzing the frequencies in a signal, they miss a crucial piece of the puzzle: how those frequencies evolve over time. Spectrograms solve this by combining time and frequency into a single intuitive image, making it perfect for analyzing music, speech, and beyond. In this post, I explore: 👉 The basics of spectrograms and how to interpret them. 👉 The Short-Time Fourier Transform (STFT) and its role in generating spectrograms. 👉 How Mel Spectrograms and MFCCs bring us closer to how humans perceive sound. Whether you're curious about audio analysis, working on machine learning projects, or just fascinated by how we can "see" sound, this blog is for you! Your thoughts and feedback are always welcome! If you enjoy the blog, feel free to share it with others who might find it useful. 😊 #AudioAnalysis #MachineLearning #Librosa #Spectrograms #DataScience

𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐊𝐞𝐲 𝐌𝐞𝐭𝐫𝐢𝐜𝐬 𝐢𝐧 𝐂𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐀𝐮𝐝𝐢𝐨 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 Nowadays, the scope of audio extends far beyond simple sound files to include elements like voice commands and AI voice assistants such as Alexa, Siri, and Cortana, as well as network-transmitted soundwaves. Here, audio quality testing is essential for maintaining high sound reproduction standards. This testing, combining scientific principles and meticulous evaluation, is conducted to minimise the risk of inconsistencies, distortions, or other issues that could degrade the overall user experience. >> Learn more: https://bit.ly/48l44CP 

ML-based noise cancellation typically involves training models on large datasets containing both clean and noisy audio. These models learn to identify and suppress noise while preserving the original sound. Compared to traditional noise reduction techniques, machine learning offers adaptive solutions that improve over time and work in a variety of noisy environments. If you want a more detailed explanation, you can either ask about the technology or view the video to get insights into how ML-driven noise cancellation is applied to improve audio experiences. https://lnkd.in/dUnRwP5a #NoiseCancellation #MachineLearning #MLAudio #AudioTechnology #SuperiorAudio #SoundQuality #AIForAudio #AIInnovation #ClearAudio #TechForGood #SmartAudio #AudioEngineering #AIInAudio

Please read the article below to see my take on the state of Class-D amplification. https://lnkd.in/e8r7Y8gz

🎶🔊 Unlock the power of sound with Diamond Audio! 💎 Join John Catalano as he dives into the importance of DSP (Digital Signal Processing) and how it transforms your listening experience. From crystal-clear highs to deep, rich lows, DSP is the secret behind perfectly tuned audio. 🎚️✨ Ready to hear the difference? Let’s amplify your sound to the next level! 🚀 #DiamondAudio #SoundPerfection #DSP #AudioEngineering #JohnCatalano #NextLevelSound #SoundEngineering #AudioInnovation #DigitalSignalProcessing #AudioExperience #SoundQuality #HiFiSound #AudioTechnology #MusicProduction #SoundDesign

📣 Exciting news for developers in the audio tech space 🌟 BigVGAN v2 is here to revolutionize audio synthesis, delivering unparalleled quality and speed. 🎧✨ https://nvda.ws/47nyYdp ✅ Top-notch Audio Quality ✅ Faster Synthesis ✅ Pre-trained Checkpoints ✅ High Sampling Rate Support Dive into the future of audio synthesis with BigVGAN v2 and create sounds that are indistinguishable from the real thing 👀🌐💡 #BigVGANv2 #GenerativeAI

Curious about how audio signals are analyzed? Here's a quick and simple explanation of FFT and magnitude normalization. Together with Dinmukhamed Sailaubek

New paper alert! Stable Audio Open is out. Open generative models are crucial for the community, enabling fine-tunes and serving as benchmarks for new models. Unfortunately, most text-to-audio models remain private, limiting access for artists and researchers. This latest work introduces a new open-weights text-to-audio model, trained with Creative Commons data. Cool! Start here: https://lnkd.in/eYcFhA7m