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Combining Speech Recognition and Diarization in one model
Combining Speech Recognition and Diarization in one model

A new approach towards multi-speaker speech processing integrates Speaker Diarization and Automatic Speech Recognition in a unified framework. We discuss the key insights from this recent exciting development in Speech AI research.

How DALL-E 2 Actually Works
How DALL-E 2 Actually Works

How does OpenAI's groundbreaking DALL-E 2 model actually work? Check out this detailed guide to learn the ins and outs of DALL-E 2.

What AI Music Generators Can Do (And How They Do It)
What AI Music Generators Can Do (And How They Do It)

Text-to-Music Models are advancing rapidly with the recent release of new platforms for AI-generated music. This guide focuses on MusicLM, MusicGen, and Stable Audio, exploring the technical breakthroughs and challenges in creating music with AI.

Residual Vector Quantization RVQ for Neural Compression
What is Residual Vector Quantization?

Neural Audio Compression methods based on Residual Vector Quantization are reshaping the landscape of modern audio codecs. In this guide, learn the basic ideas behind RVQ and how it enhances Neural Compression.

How RLHF Models Works - Reinforcement Learning From Human Feedback
How RLHF Preference Model Tuning Works (And How Things May Go Wrong)

Large Language Models like ChatGPT are trained with Reinforcement Learning From Human Feedback (RLHF) to learn human preferences. Let’s uncover how RLHF works and survey its current strongest limitations.