Audio and Speech Labeling Services by Industry Practitioners

We work with a broad range of speech and audio data, including single-speaker and multi-speaker recordings, long-form calls and meetings, voice assistant and IoT audio, in-cabin automotive recordings, clinical dictation, captioning workflows, and others.

Our workflows cover transcription, timestamped segmentation, speaker-separated tracks, and classification or attribute tagging.

On the format side, we are set up for common audio inputs such as MP3 and WAV, with cloud-based ingestion and audio processing workflows designed for scalable annotation.

We combine upfront scope alignment, approved annotation guidelines, pilot calibration, staged production reviews, and both manual and automated QA.

Depending on the task, our quality controls can include ground-truth validation, IoU checks for timestamped segment matching, and WER/CER-based evaluation for transcription quality.

We also provide clear QA reporting with each delivery stage so quality is visible and measurable throughout the project.

Yes. We support multilingual transcription and can adapt workflows for dialect- and accent-specific audio.

For each project, we define annotation schemas tailored to your data and requirements, including different languages, pronunciation patterns, accents, and other speech variations.

This can include multiple transcription attributes within the same segment when needed, allowing us to handle dialect-specific use cases more accurately instead of forcing everything into a single generic transcription workflow.

We start with a pilot project to align on the scope, schema, and acceptance criteria before scaling production. From there, our trained in-house annotation team follows project-specific guidelines in a workflow tailored to your use case, while reviewers and automated checks validate segments, transcripts, and attributes against agreed metrics.

Any discrepancies are caught early through staged deliveries and QA summaries, which helps keep annotation quality consistent from the first batch through final handoff.

We don’t have a strict minimum in terms of data volume. Instead, we approach each project based on its complexity, annotation type, and quality requirements.

For example, labeling 100 images with one object per frame using bounding boxes might take just a few hours. But 100 images with 10+ objects per frame, labeled with polygons or instance masks, would be significantly more time-consuming and costly. Because of this variability, we scope projects individually and provide a tailored quote after reviewing your dataset and requirements.

That said, our minimum project budget starts at $5,000. This helps ensure we can allocate the right experts, maintain quality control, and deliver results that meet our standards. If you're unsure whether your project fits, feel free to reach out — we're happy to review your data and advise.

Our typical turnaround time for contracted projects is approximately 1 month, though we always strive to deliver results faster when possible.

Absolutely. We maintain a team of 300+ qualified annotators that we can scale up or down based on your volume requirements. We can also adjust our resources to match your data collection and training workflow and provide continuous annotation support through our subscription service model.

Your data will be handled by our in-house team of annotation specialists. Each team member has undergone comprehensive training and has experience with dozens of annotation projects, ensuring consistent, high-quality results.

Getting started is simple. Fill out our contact form to discuss your project requirements and timeline.

Yes, we encourage pilot projects. During the project evaluation stage, we offer a free proof of concept that allows us to assess your data and requirements, define the budget, demonstrate our annotation quality, and introduce you to the CVAT platform where we perform the labeling work.