Prof. Rahul Jain’s Post

Upon request, we have provided audio examples for our latest ultra-lightweight model. With a model size of only 253 KB, this noise reduction model for speech can be distributed on a double density 5¼ inch floppy disk from the 8088 era. The latency is only 32 milliseconds. Here's the link to the audio demo: https://hance.ai/minimodel

Can you repeat that, please? 📱 📞 Even today communication fails during phone calls because of bad audio. The reasons can be many: wind blowing into the microphone, noise in the background, and bad reception - to name a few. With AI audio enhancement we can combat these challenges by removing noise, and even regenerating lost audio. Today HANCE can do: - Realtime noise removal - Realtime reverb removal - Realtime stem separation ... and we're just getting started.

📣 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

📣 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/3MxMNw4 ✅ 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

🎵 Sound the trumpets! 🎺 Our latest EngiSphere article is music to our ears! 🎧 Stanford researchers have composed a masterpiece with their new Audio Transformer architecture, outperforming traditional CNNs in large-scale audio understanding. It's like giving AI perfect pitch! 🎼🤖 Dive into our latest blog post to discover how this groundbreaking approach is amplifying the potential of audio technology. From voice assistants to music recommendations, the future is sounding sweeter than ever! 🍯 💬 Discussion Question: How do you think Audio Transformers could change your daily interactions with sound-based technology? #AudioAI #MachineLearning #TechInnovation #StanfordResearch

Bark.cpp generates audio tokens in just 7ms! Initially, the 4-bit quantized Bark model produced tokens in 25ms. Switching to #SunoAi's small Bark model reduced inference times to 7ms while maintaining great audio quality!

🎧 #Day 22 of 360: Today, I dove into the fascinating world of wavelet transformers and their application in extracting domain features from audio data. 🌊🔍 Wavelet transformers offer a powerful way to analyze signals across different scales, making them particularly effective for tasks like audio feature extraction. By decomposing signals into wavelet coefficients, we can capture both time and frequency domain information with great precision. Understanding these techniques not only enhances my grasp of signal processing but also opens up exciting possibilities in fields ranging from speech recognition to music analysis. Looking forward to applying this knowledge to enhance my work in audio processing and beyond! #WaveletTransformers #AudioProcessing #SignalProcessing #MachineLearning #DataScience #ContinuousLearning

Microsoft Research introduces VASA-1, the first AI-generated video maker. It creates hyper-realistic videos from a single photograph and 1 minute of audio, with precise lip-audio sync, lifelike facial behaviour, and real-time head movements. Link: https://lnkd.in/gQ-r4xZE