Because other speech data solutions are either too expensive or too outdated.
We are problem solvers, never limiting ourselves to just one tool or “one-size-fits-all” solution to solve the complex problems we encounter every day. Our flexible platform integrates with any commercial or proprietary toolset so you have the right tool for the job.
Our pre-vetted, trained workers and trusted reviewers ensure high-quality results. In addition to our highly skilled staff, we use smart technology and customizable quality control workflows that further guarantee results of the highest accuracy.
Typical crowdsourcing companies generally do not support languages other than English, at scale. In contrast, Audio Bee has native speakers of 200+ languages working round-the-clock so you can get multilingual training data for machine learning, fast.
Audio Bee provides human-labeled data services for voice, images, text & audio
Enterprise-grade transcription service with superior quality and also matching the industry’s best turnaround time.
Improve, train and create voice-enabled apps with comprehensive speech data collection services in over 250+ languages.
Locate and classify entities in an unstructured dataset into predefined groups or segments.
We offer flexible solutions that best matches your need. Here’s two ways to typically engage with us:
Take full advantage of our managed speech data solution that offers a smart combination of our pre-vetted workforce, online work platform and a dedicated account manager to make your project run smoothly.
Already have a work platform up and running? Then you can simply tap into our workforce-only solution for your speech data collection, transcription, data labeling and segmentation/annotation needs.
We launch and scale your projects based on a structured approach for smooth and more successful delivery.
A leading service bureau in the AI/ML training data space approached us to solve their transcription quality and scalability issues. They needed a solution provider that could handle multiple languages and reliably complete up to 400 audio hours per month each for 25 languages. The project guidelines were standard, however lengthy (40+ pages on PDFs), which meant that our transcribers needed to be trained well in them.
We created a training process to train lots of transcribers in each of the 25 languages, built a recruitment process to source quality native transcribers, and started giving an output of 5 audio hours for the first month. We eventually scaled it to 20 audio hours at the minimum while handling up to 400 audio hours for a language that had a lot of data available.
A leading Chinese Language Service Provider (LSP) approached us to do transcription and proofreading of a few Nordic languages. They were struggling to find quality people and manage the costs at the same time for these languages (given the standard of living in those countries are high).
We already had a very strong network in Nordic countries and had 20+ trained transcription resources for each Nordic language and 250-1000 people that had already participated in a voice recording project. We were able to complete 1000 people voice recording projects in 6 weeks for all 4 Nordic countries. We were also able to complete 150 hour ML transcription projects within the same timeframe.