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Speech enhancement TinyML eliminates noise in IoT applications

Speech enhancement TinyML eliminates noise in IoT applications

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By Nick Flaherty

Cette publication existe aussi en Français


Ambiq has launched an open source AI framework for its Apollo low power microcontroller to removes background noise from speech on a device in real time.

The Neural Network Speech Enhancer (NNSE) is the latest addition to its neuralSPOT’s Model Zoo. This highly optimized TinyML model effectively allows clean speech capture in noisy environments such as vehicle cabins, factory floors, offices, and outdoors.

The NNSE TInyML model can capture clean speech for various applications, such as voice memo recording, voice chat, and speech recognition. The AI model is optimized to operate on devices, in real time, with minimal latency and energy utilization.

While the pre-trained model is ready to use on Ambiq development platforms, NNSE also includes software to train, convert, and deploy customized models where needed. All software has been released under the permissive BSD-3-clause license for ease of deployment and development.

As with all Ambiq Model Zoo components, NNSE includes scripts and tools to help developers add speech de-noising capabilities to their applications. It also consists of a simple graphical user interface allowing users to easily record and save the enhanced speech along with the original noisy audio on their PC for demonstration purposes.

“Ambiq’s neural network speech enhancer may be the only open-source TinyML implementation of AI-based speech de-noising for IoT endpoint devices,” said Carlos Morales, the VP of AI at Ambiq. “The highly optimized AI model will help developers get started on speech de-noising applications on Ambiq Apollo4 Plus SoC in a matter of minutes.”

While the pre-trained model is ready to use on Ambiq development platforms, NNSE also includes software to train, convert, and deploy customized models where needed. All software has been released under the permissive BSD-3-clause license for ease of deployment and development.

As with all Ambiq Model Zoo components, NNSE includes scripts and tools to help developers add speech de-noising capabilities to their applications. It also consists of a simple graphical user interface allowing users to easily record and save the enhanced speech along with the original noisy audio on their PC for demonstration purposes.

“Ambiq’s neural network speech enhancer may be the only open-source TinyML implementation of AI-based speech de-noising for IoT endpoint devices,” said Carlos Morales, the VP of AI at Ambiq. “The highly optimized AI model will help developers get started on speech de-noising applications on Ambiq Apollo4 Plus SoC in a matter of minutes.”

A Technical Preview of the open source TinyML AI model is available at github.com/AmbiqAI/nnse.git] to download and start developing.

www.ambiq.com.

 

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