Train Smarter AI with Precise Multilingual Audio Annotation!
Empower innovative voicebots, virtual assistants, and next-generation NLP solutions in diverse languages with our 99% accurate audio labeling services.
Trusted by Industry Leaders Worldwide
Types of Audio Annotation Services That We Offer
Leveraging our vetted multilingual audio labeling team to build revolutionary AI/ML models and NLP applications
Our Audio Annotation Services Workflow
Our structured audio annotation workflow is designed to align perfectly with your evolving AI training goals.
At this stage, LTS GDS works closely with the client to thoroughly understand the objectives and the scope of work through detailed requirements such as data types, desired outputs, acoustic quality, background noise challenges, accuracy benchmarks, and compliance needs. We also identify project-specific risks, such as overlapping speech, low-quality recordings, or ambiguous emotional tones. This phase ensures that our annotation approach is customized to the business's domain.
Upon contract approval, we carefully assemble a dedicated audio annotation outsourcing team based on:
-Project scale and complexity
-Required linguistic or domain expertise
-Timeline and workflow demands
Our team leaders conduct training sessions to ensure every annotator fully understands the client's annotation guidelines, quality expectations, and objectives. We also emphasize strategies to minimize bias and improve consistency, especially for projects involving subjective annotations like sentiment analysis or nuanced classifications.
We establish a communication and project management structure. Together, we build a detailed project timeline with clearly defined milestones and implement tracking tools for real-time monitoring of progress, quality, and productivity across teams.
Our audio annotation experts kick off full-scale production following the project’s specifications. During execution, we:
-Monitor productivity and quality using defined performance indicators
-Manage risks such as data sensitivity, ambiguous cases, or shifting priorities
-Provide periodic reports
We also use continuous feedback loops during this phase to fine-tune instructions or address evolving project needs.
All annotated audio data undergoes a multi-tiered QA process:
-Annotator self-checks and team-level peer reviews
-Vertical audits by linguistic and QA leads
-Final validation against your quality benchmarks
Before delivery, we run integrity checks to ensure format consistency, tag accuracy, and metadata alignment. We also host a feedback session to gather all insights for future annotation needs.
Why LTS GDS for Upcoming Audio Annotation Projects?
Outsource audio annotation to LTS GDS to bring state-of-the-art applications to market on time and on budget
Quality-first Strategies
We prioritize quality, as reflected in our 99% accuracy, prestigious awards, strict four-step review process, and DEKRA's Certificate of Conformity for Data Labeling.
Security Standards
We safeguard your data confidentiality by signing a Non-Disclosure Agreement (NDA) and enforcing stringent security measures in full compliance with ISO 27001 and GDPR standards.
Dedicated Teams
We assemble dedicated, multi-tier teams by blending experienced leaders with a well-trained annotation team, ensuring efficient management, scalability, and adaptability to business needs.
Cost-Effectiveness
Take advantage of competitive labor costs, favorable tax policies, and flexible pricing models to optimize overseas IT outsourcing projects to Vietnam for meeting diverse client requirements.
Wall of Achievement
99%
Accuracy
5M+
Data Units
11
Countries
200+
Projects
Our Case Studies
Explore how global clients leveraged our audio annotation services to unlock the potential in their AI systems.
![[Data Annotation] Apply segmentation techniques to annotate automotive datasets](https://www.gdsonline.tech/wp-content/uploads/2024/11/21-1-1024x652.webp)
![[Data Annotation] Smart Transportation Systems Project](https://www.gdsonline.tech/wp-content/uploads/2024/05/6-2.webp)
![[Data Annotation] Pizza ingredients annotation](https://www.gdsonline.tech/wp-content/uploads/2024/05/13-1024x634.webp)
Our Tools and Technologies for Audio Annotation
Leverage customized audio annotation platforms and technologies to power your AI models.
FAQs about Audio Annotation Services for ML Projects
What is audio annotation?
Audio annotation is the process of labeling audio data with metadata such as transcripts, speaker identification, emotions, background noise, timestamps, and more. This structured information helps machine learning models understand, interpret, and learn from sound data. It's a crucial step in preparing labeled datasets for training AI systems.
Can LTS GDS handle multilingual and dialect-rich datasets?
Yes. Our audio annotation team supports diverse languages and dialects, including regional variations and minority languages. We work with native or near-native speakers to ensure annotations reflect accurate phonetic, semantic, and cultural nuances. Multilingual and dialect-specific projects often involve:
- Code-switching (mixing languages in a single conversation)
- Regional slang or informal speech
- Accent and pronunciation variation
To ensure quality, we assign linguistic experts familiar with the specific locale or dialect and provide project-specific training to handle complexity.
What are the main challenges in audio annotation?
Common challenges include overlapping speech, poor audio quality, and complex accents or emotions. These can reduce model performance if not addressed properly. We overcome them with expert training, clear guidelines, and multi-layer quality checks (self-check, cross-review, vertical review, and final inspection).
What kind of audio data formats are typically supported?
LTS GDS supports all major audio formats, including WAV, MP3, FLAC, AAC, and OGG. Our team can also handle custom or proprietary formats as needed. Every file is preprocessed to ensure compatibility with your ML pipeline.
Awards & Certifications
Bring Powerful Voice & NLP Models to Market with Accurately Annotated Datasets
Connect with our experts to explore the best approach for your audio ML pipeline.
