# AI Pipeline for WordPress on n8n: Text Normalization, Translation, and TTS **Keywords:** WordPress, n8n, LLM text normalization, machine translation, speech synthesis, Google Cloud Run, reproducibility ## Abstract I present a reproducible, self‑hosted pipeline that converts WordPress articles into **multilingual voiceovers** (Italian/English). The system orchestrates **LLM‑based text cleaning**, **machine translation**, and **neural text‑to‑speech (TTS)** via **n8n**. A lightweight microservice on **Google Cloud Run** performs long‑form TTS and writes audio artifacts (`.wav`) to **Google Cloud Storage (GCS)**. Metadata and processing state are tracked through **Google Sheets**, enabling deterministic batch runs and idempotent processing. We describe the architecture, interfaces, and evaluation protocol (latency, throughput, and audio integrity checks) to facilitate reuse and extension. * * * ## 1. Problem Statement Blogs often publish long‑form content without an accessible audio counterpart. Manual conversion to voice is time‑consuming and error‑prone (HTML artifacts, punctuation issues, malformed text). The goal is to **automate** the *post → clean text → translation → TTS → publish* loop with **traceability** and **repeatability**, while keeping infrastructure **self‑hosted** for control and cost predictability. * * * ## 2. System Overview The solution is composed of three subsystems: 1. **Orchestration (n8n)** * Scheduled ingestion of WordPress posts. * Text normalization with an LLM (“Clean” nodes per language). * Optional translation to EN. * HTTP requests to the TTS microservice. * Update of two WordPress pages (IT/EN) with an `