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Knowles launches Raspberry Pi Dev Kit to enable voice integration

Knowles is making available the AISonic IA8201 Raspberry Pi Development Kit bringing voice, audio edge processing, and machine learning (ML) listening capabilities to devices and systems in a range of different industries.

Product designers and engineers will now have access to a single tool to streamline design, development, and testing of technology that will help to extend voice and audio integration in their respective industries.

“Knowles designed this kit to be the simplest and fastest way for product designers to prototype new innovations to address emerging use cases including contextually aware voice, ML listening, and real-time audio processing, that require flexible development tools to accelerate the design process, minimise development costs, and leverage new technological advances,” said Vikram Shrivastava, senior director, IoT Marketing at Knowles. “By selecting Raspberry Pi as the system host, we are opening up the ability to add voice and ML to the largest community of system developers that prefer a Linux or Android environment.”

The kit is built around the Knowles AISonic IA8201 Audio Edge Processor OpenDSP, for ultra-low power and high-performance. The audio edge processor combines two Tensilica-based, audio-centric DSP cores; one for high-power compute and AI/ML applications, and the other for very low-power, always-on processing of sensor inputs.

The IA8201 has 1MB of RAM on-chip that allows for high bandwidth processing of advanced, always-on contextually aware ML use-cases and memory for multiple algorithms for an optimal user experience.

Using the open DSP platform, the kit includes a library of on-board audio algorithms and AI/ML libraries. Farfield audio applications can be built using the available ultra-low power voice wake, beamforming, custom keywords, background noise elimination, from Knowles algorithm partners from the intelligent voice ecosystem such as Amazon Alexa, Sensory, Retune, and Alango supporting a wide range of voice and audio customisation.

The kit also features TensorFlow Lite-Micro SDK for fast prototyping and product development for AI/ML applications. This allows for porting models developed in larger cloud Tensor Flow frameworks to an embedded platform usually with limited compute and lower power consumption at the edge, for example, AI inference engines for verticals such as industrial and commercial.

With options for either two or three pre-integrated Knowles Everest microphones based on the needs of the product, the kit includes two microphone array boards to help select the appropriate algorithm configurations for the end application.

According to Knowles, by offering built-in microphone arrays that support the audio and voice capabilities on the IA8201 DSP, OEMs will have access to a high-quality, high-performance all-in-one development solution from a single supplier.

Developer support is available through the Knowles Solutions Portal for configuration tools, firmware and algorithms that come standard with the kit, allowing for complete prototyping, design, and debugging.

Author
Neil Tyler

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