Auditory Binaural Masking Level Difference (BMLD) MCP Server
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Auditory Binaural Masking Level Difference (BMLD) Skill
Zero-dependency sovereign personal agent skill for non-invasive psychoacoustic modeling of Binaural Masking Level Difference (BMLD), brainstem auditory squelch, and cocktail party speech-in-noise intelligibility.
flowchart TD
Dichotic["Dichotic Hearing Test (S0N0 vs SpiN0)"] --> Phase["Interaural Phase Difference (IPD) Extraction"]
Phase --> BMLD_Calc["BMLD dB Decibel Advantage Engine"]
BMLD_Calc --> Brainstem["Brainstem Processing & Speech Intelligibility Scoring"]
Brainstem --> Agent["OpenClaw / Hermes Personal Agent Actions"]Features
Deterministic Math: Pure Python standard library implementation with zero external dependencies.
Audiological Standard Formulas: Implements clinically validated homophasic and antiphasic decibel differential modeling.
Cocktail Party Intelligibility Modeling: Direct calculation of speech perception advantage in background noise.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: OpenClaw GenPark Vocalist
Quickstart
from client import BinauralMaskingLevelDifferenceClient
client = BinauralMaskingLevelDifferenceClient()
result = client.evaluate_bmld(
s0_n0_threshold_db=64.0,
spi_n0_threshold_db=50.0,
test_frequency_hz=500.0
)
print("BMLD:", result["bmld_db"], "dB")
print("Brainstem Score:", result["brainstem_processing_score"])
print("Classification:", result["classification"])License
Apache-2.0
This server cannot be deployed
Maintenance
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