ClinicalTrials.gov
public full text
Public Domain
Wind Noise Sound Quality Preference and Claims Study
Claims evidence is required for a new Wind Noise Canceller (WNC) algorithm. Wind noise is not sound in the classic sense, as it does not correspond to pressure waves moving through the air. However, because the microphone membranes are deflected by the wind noise, the microphones translates them into a sound signal. Since the pressure fluctuations are small in size, this wind noise signal is uncorrelated between the two HI microphones (correlation decreases with increasing microphone distance), creating bothersome sounds at low and very low frequencies. Historically, wind noise cancellers have been applied to make wind noise less bothersome. However, target signal (i.e. speech) sound fidelity can become compromised as a biproduct. Therefore, an updated wind noise canceller has been proposed to improve wind noise attenuation and target signal fidelity compared to the previous iteration. Informal exploratory testing by normal hearing Sonova employees have identified the new wind noise canceller iteration to improve sound quality ratings with some dependencies on (1) wind speed, (2) wind angle and (3) target signal. Therefore, this study will aim to produce sound quality data showing a benefit for the new wind noise canceller compared to the older version for the purpose of claim substantiation.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Deep Learning-Based Predictive Fixed-Filter Active Noise Control for Dynamic Noises#1109073
- Towards a physics-informed network paradigm with data generation and background noise removal for different distributed acoustic sensing applications.#312464
- Ouroboros: Self-Referential Backdoor Attacks on Speech Enhancement via Clean Audio Triggers#622444
- CLEAR: Online Speech Content Leakage Estimation through Cross-ASR Disagreement#1104614
- Prediction of Interactional Aerodynamic Noise of Propellers and Wing Using High-Fidelity CFD#1119933
Record · ID 1163352
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive