Case Studies

AI-Powered Publishing in Practice

With a long-term focus on print and digital publishing, Linking Publishing launched the 'Intelligent Audiobook Generation Platform' project to address the rapid growth of digital reading and smart content. The goal is to build an automated voice generation workflow that transforms static text into dynamic, character-driven audiobooks, deepening the reader's experience and establishing a scalable production system for the publishing industry.

Project Challenges

Efficient and Accurate Text Parsing and Semantic Analysis

The system needs to quickly perform automatic analysis of text structures like chapters, paragraphs, and sentences, while also identifying semantic elements such as characters, tone, and emotion.

Automated Character Voice Identification and Casting

It must effectively distinguish between narration and character dialogue, automatically applying a suitable voice logic based on character traits to reduce manual intervention.

Cross-Lingual and Regional Management Capabilities

The system should support processing of both Chinese and English content and be able to implement character and licensing management rules for different publishing regions.

Stable Processing and Fault Tolerance

To ensure high-quality audio output, the platform requires stable processing performance and an automatic recovery mechanism to handle diverse and complex source materials.

Logic Reconstruction

Rebuilding Voice Logic with a Character-Centric Core

Centered on character identification, this design integrates voice parameters with emotional expression to boost content immersion and recognition. Each audio output corresponds to a character's traits, making the listening experience more dramatic and coherent.

Logic Reconstruction

Intelligent Workflow

Establishing a Complete Intelligent Production Process

Integrates the entire workflow from file upload, text parsing, semantic analysis, and character tagging to final audio output, automating every stage. The system also supports module reuse and content version tracking, improving production efficiency and consistency.

Intelligent Workflow

Control and Planning

Planning Identification Thresholds and Stability Controls

Quality benchmarks and fault-tolerant logic are set for each stage—character identification, semantic tagging, and voice synthesis—ensuring stable output even in highly complex text scenarios and reducing the risk of error propagation.

Control and Planning

Technical Architecture Highlights

The system architecture is designed around character-driven automation, creating a scalable and reusable intelligent publishing production chain.

Modular Semantic Parsing

Automatically parses chapters, paragraphs, and sentences to identify characters, tone, and emotional elements, forming the foundation for voice generation.

Character-Based Voice Mapping

Automatically distinguishes between narration and character lines, assigning corresponding voice profiles based on character attributes to enhance immersion and identifiability.

Automated Production Workflow

The entire process, from upload and parsing to voice generation and output, is fully automated, reducing manual effort and error rates.

Multi-language and Rights Management

Supports both Chinese and English, with modular voice models and regional licensing controls, making it adaptable for various publishing scenarios.

Project Results & Client Feedback

梁家瑞

Product Manager

梁家瑞 Logo

TWJOIN's professional development capabilities allowed us to seamlessly integrate multiple AI functions, ensuring our product runs perfectly. They are an outstanding software development partner.

Built the industry's first character-driven intelligent audiobook generation platform, enhancing the automation of publishing production.

Supports bilingual (Chinese/English) processing and modular character management, facilitating multi-language publishing and cross-border distribution.

Intelligently automated the traditionally labor-intensive process of character semantic analysis, significantly reducing production costs.

Enhanced the contextual feel and recognizability of audio content, strengthening reader experience and market competitiveness.

Successfully guided the publisher toward an AI-driven content creation model, marking a milestone in intelligent publishing.

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