Generative deep learning models have transformed NLP, CV, speech processing, and TTS. Large language models demonstrate versatility in NLP, while pre-trained models excel in CV tasks. Amazon AGI’s BASE TTS, trained on extensive speech data, improves prosody rendering. It introduces novel discrete speech representations, promising significant progress in TTS. For more details, visit the Paper.
Recent Advancements in AI and Practical Solutions for Middle Managers
Recent advancements in generative deep learning models have revolutionized fields such as Natural Language Processing (NLP), Computer Vision (CV), Speech Processing, and Text-to-Speech (TTS). These advancements have led to the development of large language models (LLMs) in NLP and pre-trained models in CV that can perform diverse tasks with minimal explicit guidance.
In the realm of Speech Processing and Text-to-Speech (TTS), models now leverage thousands of hours of data to produce speech that is increasingly closer to human-like quality. For instance, Amazon AGI has introduced BASE TTS, a large TTS (LTTS) system trained on approximately 100K hours of public domain speech data. BASE TTS is designed to model the joint distribution of text tokens and discrete speech representations, known as speech codes, and can capture complex probability distributions of expressive speech, thus improving prosody rendering compared to early neural TTS systems.
AI Solutions for Middle Managers
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
For AI KPI management advice, connect with us at hello@itinai.com. And for continuous insights into leveraging AI, stay tuned on our Telegram or Twitter.
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