Vendor: Ceva, Inc. Category: Edge AI Accelerator

Neural-network-based noise cancellation

In a world where videoconferencing, team gaming, and voice-operated systems proliferate, it is vital to extract clear, intelligib…

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Overview

In a world where videoconferencing, team gaming, and voice-operated systems proliferate, it is vital to extract clear, intelligible voice from environmental noise. Ceva-ClearVox ENC software features a neural-network-based ENC algorithm with small memory and processing requirements to embed ENC into even tiny systems. The algorithm processes both outgoing and incoming speech to provide clear communications to both parties on a call

The Solution

Ceva-ClearVox ENC implements a trained neural network in embedded software, eliminating the need for external cloud connectivity. Despite the neural-network approach, ClearVox ENC requires so little memory and processing power that it can be coresident with other applications even in tiny hardware configurations. Yet the algorithm is effective enough to give excellent speech quality for videoconferencing and gaming.

Working with a single microphone input for outgoing speech and—uniquely—also processing incoming signals from the other parties in a connection, ClearVox ENC effectively separates speech from both continuous and transient background noise. Versions are available for Ceva-BX1, BX2, and SensPro2 DSP cores and for ARM MCUs.

Key features

  • Embedded, neural-network-based algorithm requires only a single microphone.
  • Local processing means no Internet latency or cloud-AI privacy issues.
  • Bidirectional processing cancels noise on both outgoing and incoming signals.
  • 16 kHz sampling rate and 16-bit resolution ensure high speech quality and cancellation of broad-spectrum and high-frequency environmental noise.
  • Optimized code requires little memory space or processing power, allowing use in small systems even in conjunction with other applications.

Block Diagram

Ceva-ClearVox ENC block diagram

Benefits

  • Using a trained, optimized, and highly compact neural network, ClearVox ENC effectively separates clear voice signals from both continuous and transient ambient noise, yielding intelligible speech even with adverse environmental noise. The ClearVox ENC algorithm requires only a single local microphone, and uniquely processes both outgoing and incoming speech. Thus both parties in a conference or gaming environment benefit from the ENC.
  • The software requires minimal memory space and computing power, so it can be run effectively even in quite small systems, and in conjunction with other applications, such as Ceva-RealSpace.

Applications

  • Consumer IoT
  • Automotive
  • Mobile
  • PC 

Specifications

Identity

Part Number
Ceva-ClearVox ENC
Vendor
Ceva, Inc.
Type
Silicon IP

Videos

MWC BARCELONA 2018 CEVA CLEARVOX DEMO
Far Field Voice Controlled smart speaker reference design

Files

Product Sheet Download

Note: some files may require an NDA depending on provider policy.

Provider

Ceva, Inc.
HQ: USA
Contact Ceva, Inc.

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Frequently asked questions about Edge AI Accelerator IP cores

What is Neural-network-based noise cancellation?

Neural-network-based noise cancellation is a Edge AI Accelerator IP core from Ceva, Inc. listed on Semi IP Hub.

How should engineers evaluate this Edge AI Accelerator?

Engineers should review the overview, key features, supported foundries and nodes, maturity, deliverables, and provider information before shortlisting this Edge AI Accelerator IP.

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