The hottest Text-to-Speech Substack posts right now

Working with AI models often requires subscriptions that cost money, but running your own LLM locally can be done with open-source models like Llama 2.
Spring Text-to-Speech project involves using Spring framework with HTTP exchange interfaces and RestClient class for mp3 generation from text.
Spring AI project is still in early versions, like 0.8.0-SNAPSHOT, with possible changes and bugs, making preparations for a training course challenging.

OpenAI introduced Sora, a text-to-video model capable of creating detailed videos up to 60 seconds long with vibrant emotions.
Meta AI unveiled V-JEPA, a method for teaching machines to understand the physical world by watching videos, using self-supervised learning for feature prediction.
Google announced Gemini 1.5 Pro with a context window of up to 1 million tokens, allowing for advanced understanding and reasoning tasks across different modalities like video.

The latest innovation in Generative AI focuses on Speech Models that can produce human-like voices, even in songs.
Self-Supervised Learning is revolutionizing Text-to-Speech technology by allowing models to learn from unlabelled data for better quality outcomes.
Text-to-Speech systems are structured in three main parts, utilizing models like TORTOISE and BARK to produce expressive and high-quality audio.

Neets.ai is a platform for AI characters that can have real-time video and audio interactions.
The platform involves advanced technology like AI text-to-speech and real-time video generation.
DL Software is a company focused on artificial intelligence applications, including artificial general intelligence.

Generative AI field is rapidly evolving with new models for text, image, and speech generation.
Models need to encode semantics into tokens and generate media from those tokens.
Combining modalities like speech and text requires advanced decoders to improve performance.

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Amazon has developed a new, massive text-to-speech model called BASE TTS with emergent abilities, enhancing its natural speech capabilities for AI assistants like Alexa.
The 980 million parameter BASE TTS model is significant for audio and NLP advancements, as it's the largest text-to-speech model created so far.
Text-to-speech and NLP innovations are paving the way for more human-like interactions with voice assistants, marking a shift towards ambient computing.

Recording audio input from a microphone is a simple first step
Using OpenAI Whisper for voice to text conversion is an easy and effective process
Experiment with different models for generating responses and improving text-to-speech capabilities

Coqui TTS is a deep learning toolkit for Text-to-Speech with quick installation and decent output.
Supports multiple TTS models and allows fine-tuning.
Underlying XTTS model is not open-source, and the cloned voice may not be perfect.

High-quality data is essential for training accurate and natural-sounding text-to-speech AI models.
Cutting-edge tools like annotation software and ASR services are pivotal for efficient data collection in developing text-to-speech AI models.
Collaboration and data sharing drive innovation in the AI community, enhancing the representation of diverse perspectives and voices in AI-generated speech.