Flowedit Associative Memory Lifelong Pronunciation

---
name: flowedit-associative-memory-lifelong-pronunciation
description: FlowEdit introduces lifelong adaptation for frozen TTS models using Modern Hopfield Networks as content-addressable episodic memory, enabling pronunciation corrections without weight updates.
created: 2026-06-20
source: arXiv:2606.20518
authors: Harshit Singh, Ayush Pratap Singh, Nityanand Mathur
tags: [associative-memory, flow-matching, lifelong-learning, pronunciation-adaptation, modern-hopfield, neuroscience]
category: ai_collection
---

# FlowEdit: Associative Memory for Lifelong Pronunciation Adaptation in Flow-Matching TTS

## Overview

FlowEdit introduces a lifelong adaptation framework for frozen flow-matching text-to-speech (TTS) systems using Modern Hopfield Networks as content-addressable episodic memory for pronunciation corrections.

## Core Methodology

### Modern Hopfield Network Memory
- Content-addressable storage for corrections
- Fuzzy morphological matching via soft attention
- Fast convergence, high capacity, noise tolerance

### Latent Conditioning Edits
- Token-level perturbations in text embedding space
- Learned edits rather than weight updates
- Gradient-based optimization with supervised feedback

### Lifelong Learning Paradigm
- Continuous incremental corrections
- No catastrophic forgetting
- Similarity-gated retrieval

## Neuroscience Foundations

**Hopfield Network Analogy:**
- Hippocampal pattern completion modeling
- Content-addressable recall mechanisms
- Energy-based memory dynamics

**Episodic Memory Formation:**
- Single-trial learning of corrections
- Cue-dependent retrieval
- Contextual binding

## Experimental Results

- 312 multilingual proper nouns across 18 language families
- Phoneme Error Rate reduction: 92.7%
- Correction time: ~15 seconds

## Trigger Words

flow-matching, associative memory, modern hopfield, lifelong learning, episodic memory, hippocampal, pattern completion

## Related Concepts

- Modern Hopfield Networks
- Flow-matching generative models
- Episodic memory formation
- Content-addressable memory