Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS+ICA Algorithm

Area of Science:

• Engineering
• Computer Science
• Human-Computer Interaction

Background:

• Smart Home (SH) environments require robust systems for voice control, encompassing building automation, visualization, voice command recognition, and noise cancellation.
• Existing systems often face challenges with background noise interference in real-world SH settings.
• Integration of diverse technologies is crucial for effective voice-activated smart home functionality.

Purpose of the Study:

• To develop and evaluate an innovative voice control system for operational and technical functions within a real Smart Home environment.
• To assess the performance of noise-canceling algorithms in improving voice command recognition accuracy amidst various household noises.
• To demonstrate the feasibility of a comprehensive voice control solution using established automation and software tools.

Main Methods:

• Utilized KNX technology for building automation and LabVIEW software for visualization, data connectivity, and noise-canceling calculations.
• Implemented Microsoft Windows OS speech recognition software for command interpretation.
• Applied Least Mean Squares (LMS) algorithm and Independent Component Analysis (ICA) for additive noise canceling from speech signals.
• Conducted experiments in a real SH environment with simulated noise from a television, vacuum cleaner, washing machine, dishwasher, and fan.

Main Results:

• The developed voice control system demonstrated a high success rate, exceeding 95% in recognizing voice commands.
• Performance was evaluated across various additive noise conditions typical of a Smart Home.
• The integration of KNX, LabVIEW, and specific noise-canceling algorithms proved effective in a practical setting.

Conclusions:

• The proposed approach offers a robust and highly accurate voice control solution for Smart Home applications.
• Effective noise cancellation is critical for reliable voice command recognition in complex domestic environments.
• The successful integration of KNX, LabVIEW, and Windows speech recognition provides a viable framework for advanced smart home automation.