Infant Pronunciation Correction Lip-Reading Speech Recognition Data Labeling & Dataset Construction Case Study

Voice · Video AI Training Data Construction Case Study

Infant Pronunciation Correction Lip-Reading Speech Recognition Data Labeling & Dataset Construction Case Study

Industry: Education · EdTech

For an AI-based pronunciation correction service that analyzes children’s lip movements and speech simultaneously, Gendive executed end-to-end construction of video and audio-based lip-reading AI training data—from planning and data collection to data labeling, refinement, and structured processing.

Project Overview

The client requested high-quality AI training data in JSON format, including synchronized lip-reading videos captured from multiple angles and aligned audio recordings of children aged 6–12, along with structured speech scripts and a rigorous data labeling and quality review process.

Data Type: Children’s facial video (mp4) + synchronized audio (wav) + script text
Labeling Scope: Sentence-level transcription & refinement, speech segment timestamp alignment, metadata tagging (speaker, age, etc.)
Participants: Several hundred children aged 6–12, with differentiated script volumes by age group
Delivery Format: JSON structure linking video, audio, and text into an integrated dataset construction
Key Requirements: Multiple camera angles suitable for lip-reading model training, stable speech quality, and strict compliance with child data privacy and consent procedures
Quality Objective: Achieving labeling quality and structured review processes sufficient for immediate AI model training

Key Work Scope

Due to the nature of working with children, this project required detailed execution across all stages—from script design and filming environment setup to transcription, refinement, and multimodal data consistency validation.

TASK	Description
Requirement Analysis & Design	Defined lip-reading training requirements for pronunciation correction services. Designed script volume, camera angles, and JSON data schema based on age-specific speech difficulty and sentence length.
Child Script Planning	Developed dozens to hundreds of sentences per age group (6–9, 10–12), focusing on words and sentences meaningful for pronunciation correction and ensuring natural readability for children.
Simultaneous Video & Audio Recording	Captured mp4 videos from multiple angles (front, side, etc.) to clearly show facial and lip movements, while simultaneously recording high-quality wav audio. Standardized filming conditions to minimize data variance.
Speech Transcription & Text Refinement	Transcribed collected speech at the sentence level, removed typos and unnecessary utterances (hesitations, repetitions), and standardized text according to language norms for model training suitability.
Metadata Tagging & Quality Review	Tagged metadata such as age, gender, camera angle, and recording environment. Conducted two-stage sample-based reviews to verify transcription accuracy and audio-video synchronization. Reprocessed and revalidated error cases.
Multimodal Data Alignment Processing	Using in-house annotation tools, aligned mp4 video, wav audio, and transcribed scripts based on timestamps and mapped them into a JSON structure. Ensured consistent segment definitions and file paths for lip-reading model training.

Project Workflow

1. Requirement Definition · Schema Design

2. Script & Filming Guide Design

3. Lip-Reading Video & Audio Collection

4. Speech Transcription & Text Refinement

5. Metadata Tagging · 1st & 2nd Review

6. JSON Structuring · Final Delivery

Gendive Partner Data Labeling Services

In sensitive domains such as children, healthcare, and voice/video data, successful data labeling depends not only on workforce deployment but on strong project management capabilities.

What Differentiates Gendive

We go beyond execution—participating from requirement definition to schema design to ensure data structures align with the client’s AI model objectives.
Through standardized guidelines and multi-stage review processes, we maintain consistent labeling quality even as projects expand or repeat.
With experience in sensitive data projects, we proactively manage consent forms, personal information, and portrait rights issues to reduce client risk and operational burden.

In voice and video-based services such as children’s pronunciation correction, data quality directly determines service quality. If you require a data labeling consultation or AI training dataset construction, please contact us through the channel below.

We will collaboratively design optimal collection, labeling, and review strategies aligned with your project scope, budget, and timeline.

Request a Data Labeling Consultation

Request AI Training Dataset Construction

Contact: Gendive Data Team

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