This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using time-warping ...

Discover why robots excel at math but struggle with human-like tasks. Explore Moravec's Paradox and the future of adaptable ...

Amid the trade war with the US, Beijing’s regime is prioritizing technology as a key driver of economic and political power ...

The performance of automatic speech recognition is severely degraded in the presence of noise or reverberation. Much research has been undertaken on noise robustness. In contrast, the problem of the ...

Speech and Natural Language Processing is a rapidly evolving field at the cutting edge of AI and Computer Science. This course presents the core theories, models and algorithms to enable the ...

But what truly sets Sirius apart lies under the hood: an AI head with up to 5 TOPS of edge computing power, large model-driven interaction capabilities, and a modular platform that supports ...

In this paper, an improved method of model complexity selection for nonnative speech recognition is proposed by using maximum a posteriori (MAP) estimation of bias distributions. An algorithm is ...

An increasing number of users are forming deep emotional bonds with AI chatbots, leading to a new form of addiction - AI ...

Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning. As AI continues to expand, ...

Did you know speech disorders in children have more than doubled since the pandemic? At the same time, the National ...

Enterprises adopting voice AI must consider not just usability, but inclusion. Supporting users with disabilities is a market opportunity.

As we build machines that listen not just to our words but to our emotions, the responsibility to use that power ethically ...