Responsibilities

• Verification of Speech Data
• Validate speech data related to STT, TTS and wake-up word detection to ensure accuracy and consistency.


• TTS Data Collection Strategy & Execution
• Design and implement data collection strategies that reflect North American linguistic and cultural characteristics.
• Secure high-quality English, Spanish, and French text and speech data from diverse sources (e.g., online media, audio archives, user interviews).


• Data Quality Control
• Review collected data for pronunciation, intonation, grammar, and vocabulary accuracy to ensure suitability for model training.
• Perform outlier detection and data cleaning tasks (e.g., noise removal, audio clipping, text normalization).


• Process Automation & Optimization
• Develop scripts and tools (using Python, R, etc.) to automate repetitive tasks in data collection and verification.
• Build and manage data pipelines and propose workflow improvements to optimize the process.


• Outsourcing Management
• Oversee and manage outsourcing agencies responsible for speech data labeling, ensuring adherence to quality standards and deadlines.


• Collaboration & Communication
• Work closely with development teams, speech engineers, and language experts to set data quality standards and project objectives.
• Provide regular reports on project progress, challenges, and improvement measures.


• Market & User Analysis
• Analyze language usage trends, dialects, and intonation patterns in North America to continuously refine data collection strategies.
• Incorporate user feedback and emerging research trends to update and improve the datasets.

Qualifications

• Experience
• Over 3 years (or equivalent experience) in voice signal-related roles, including speech data verification, labeling, and managing outsourcing agencies.
• Proven experience in collecting and validating speech data for various audio signal tasks.


• Educational Background
• Bachelor’s degree in Linguistics, Speech Signal Processing, Computer Science, Data Science, or a related field.
• A Master’s degree or higher with relevant research experience is preferred.


• Language & Communication Skills
• Trillingual native-level proficiency in English, French, and Spanish is essential.
• Strong understanding of North American dialects and cultural nuances is required.
• Excellent documentation, presentation, and teamwork skills.
• Professional-level Korean language proficiency is an asset for research collaboration.


• Project Management & Problem-Solving
• Strong analytical, problem-solving, and project management skills, with the ability to handle multiple tasks and set priorities effectively.

Preferred

• Specialized Industry Experience
• Proven track record in quality control and management of audio data labeling projects.
• Strong understanding of technologies related to STT, TTS and wake-up word detection.
• Project experience in this field and hands-on experience with deep learning frameworks such as TensorFlow and PyTorch.


• Data Management Expertise
• Experience in building and managing large-scale multi-modal (text + speech) datasets and optimizing data cleaning processes.


• Sound Engineering & Narration Directing Expertise
• Demonstrated experience in sound engineering, including designing and optimizing acoustic environments, implementing advanced audio processing techniques, and ensuring high-quality sound production for various applications.
• Proven track record in narration directing, managing voice talent, and providing creative guidance to ensure that voice-over projects align with brand or project objectives.
• Proficiency in using industry-standard audio production tools and software (e.g., Pro Tools, Adobe Audition) is highly desirable.


• Professional & Academic Engagement
• Active participation in industry conferences, seminars, or workshops, with contributions to patents, academic publications, or open-source projects.


• Certifications
• Relevant certifications in cloud services, data engineering, or machine learning (e.g., AWS Certified Solutions Architect, Google Cloud Professional Data Engineer) are a plus.

Recruiting Process

• Application Screening - Coding Test - First Interview - Second Interview - Offer Negotiation - Final Acceptance
• The recruitment process may differ based on the specific role and may be subject to changes depending on schedules and circumstances.
• Applicants will be notified of the application schedule and results individually via the email address provided in their application.

Please refer to the videos from KCCV 2022 and UMOS Day 2021 for insights into 42dot Autonomous Driving, our autonomous driving AI software.

Please upload all submission files in PDF format.

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