The quality of your AI solution relies heavily on the quality of the data used to train it. We harness the intelligence, skills, and cultural knowledge of our global community of contributors to create custom datasets for your machine learning applications.
We collect and/or create diverse and representative datasets via our large and vetted global community. Harnessing human intelligence in a manner that reduces bias is key to successful machine learning.
Linguistic annotation, also known as corpus annotation, is the tagging of language data in text or spoken form. Linguistic annotation seeks to identify and flag grammatical, phonetic and semantic linguistic elements within a body of text or audio recording. Utilizing our global linguistic experts, we can find qualified annotators native in the language of your corpus or the target language of your NLP model.
We can source thousands of contributors native in languages and dialects. We can create custom handwritten data tailored to your specific project. You dictate the languages required, what our contributors write, and how they write it. We’ll then assess the data for quality and formatting before packaging it according to your specifications.
When designing and developing your chatbot application, you need to have a good understanding of utterances. Utterances are the input from the user which the chatbot needs to derive intents and entities from. To train any chatbot to accurately extract intents and entities from the user’s dialog input, it is imperative to capture a variety of different example utterances for each and every intent.
From virtual assistants to in-car navigation systems, all sound-activated machine learning systems rely on a foundation of diverse, high-quality audio data. If you’re looking for professionally recorded speech data or need a remote community to conduct software testing, we are your solution for audio data outsourcing.