Audio Transcription

We provide large scale transcription for audio files of different frequencies across 130+ languages. Our team can work on your platform or use our own to create an accurately annotated transcript for your ML model. We support transcript formats across multiple platforms, annotating events, entities and relations as required by your model.

Text Labeling

Text labeling involves annotating text to identify the type of text or specific bits of text. This allows your NLP models to understand the text and process it. Properly labelled data can make a big difference. Considered an important step in your NLP pipeline, we make it easy for you to have the right labeled data for production inference.

Text Classification

Whether you require search engine results to be classified or you need sentiment analysis for user feedback, our team will provide multilingual text classification for your machine learning models. As part of a supervised learning approach to your project, we deliver painstakingly accurate text classification to get it right the first time.

Audio Classification

Annotators listen to an audio file and identify its content, classify it into one of the different categories that are either pre-determined or discovered from the audio. Examples include identifying topics discussed in an audio, the type of content in audio such as music, news, natural conversations or identifying background audio such as chatter, nature etc.

Entity Recognition

We offer multilingual named entity recognition (NER) service. Our annotators go through large volumes of text in their own language and identify entities such as people's names, places, references and much more. Machine learning models can benefit from our named entity recognition to understand the content much better and infer more accurately in a production environment.

Handwritten Text Transcription

Applications such as optical character recognition (OCR) processors require large datasets of typed text to understand handwritten scripts. We offer transcription of handwritten text in over 130+ languages. Handwritten transcription is helpful for machine learning models to learn how to recognize text across a variety of scripts and writing styles, in the language in which it was written.

Chatbot Localization

Chatbots have become commonplace on websites and apps, however, lack of proper chatbot localization has caused a decline in usage beyond the English speaking demographics. At Hybrid Lynx we understand how chatbots should be localized to interact with speakers of local markets. We offer utterance localization and variant creation to ensure your chatbot feels native to users.

Linguistic Annotation

Chatbots, spam filters, search engines and other applications benefit from linguistic annotation to understand contexts using parts of speech (POS) tagging, phonetic, semantic and, discourse annotation as well keyphrase tagging. From small to large clients, we offer a reliable solution that includes the workforce and a platform for short burst or longterm projects.

Entity Linking

Detecting and finding entities that are ambiguous in a text through a knowledge corpora is known as entity linking, which comprises of metadata addition to identify the type and appearance of an entity in the text. Entity linking is important for building intelligence in models that need to understand interaction via text and voice. Let's discuss how we can help with your entity linking requirements.

Human-in-the-Loop Custom Data Annotation & Labeling Services

Leverage our crowd of over 10,000 annotators for training of your machine learning models