Environmental Noise Cancellation (ENC): Part 2 - Noise types and classic methods for Speech Enhancement
In part 1, we discussed some important concepts related to sound processing and environmental noise cancellation that are essential to keep in mind when designing an ENC (Environmental Noise Cancellation) system. Now, let’s talk about the rest of the equation, which is the noise itself. In this section, we will characterize common noise types and explore some of the classical speech enhancement methods that are commonly used to tackle this problem.
Researchers typically categorize noises as either stationary or non-stationary, depending on different characteristics. Understanding the differences between these two types of noise can provide valuable insights into their properties and ways to deal with them.
Stationary noise refers to noise that remains relatively constant in its statistical properties over time. In other words, its statistical characteristics such as mean, variance, and autocorrelation remain constant or change only slightly over time. Common examples of stationary noise include the hum of an air conditioner or the constant hum of a refrigerator. Stationary noise can often be easily characterized and analyzed using mathematical techniques, making it suitable for various analytical algorithms to predict and cancel.
To read the full article, click here
Related Semiconductor IP
- NPU IP Core for Mobile
- NPU IP Core for Edge
- Specialized Video Processing NPU IP
- HYPERBUS™ Memory Controller
- AV1 Video Encoder IP
Related Blogs
- Unveiling Ultra-Compact MACsec IP Core with optimized Flexible Crypto Block for 5X Size Reduction and Unmatched Efficiency from Comcores
- Synopsys and Arm Collaboration - Accelerating Development and Innovation for Arm-based Automotive Systems
- Faster, Higher Capacity Emulation and Prototyping for AI Workloads
- A Fast and Seamless Way to Burst to the Cloud for Peak EDA Workloads
Latest Blogs
- Cadence Extends Support for Automotive Solutions on Arm Zena Compute Subsystems
- The Role of GPU in AI: Tech Impact & Imagination Technologies
- Time-of-Flight Decoding with Tensilica Vision DSPs - AI's Role in ToF Decoding
- Synopsys Expands Collaboration with Arm to Accelerate the Automotive Industry’s Transformation to Software-Defined Vehicles
- Deep Robotics and Arm Power the Future of Autonomous Mobility