NLP & Speech Technology

Enhance your Natural Language Processing and Machine Learning solutions with our top-grade training data

NLP requires a lot of adeptly handled, labeled and organized training data to work in the real world. Our global crowd of over 1 million contributors is present in over 170 countries and speak over 235 languages and dialects, enable access to rich and diverse training data to help build robust conversational AI.

VIDEO: See how Appen can help you build world-class NLP & speech models with high quality data

End-to-End Data Collection:

Text Collection

To build world class language-based ML applications interpreting textual data from a variety of sources, we offer multilingual Text Data Collection Services in all major languages and dialects. Our Text Utterance Collection and Text Generation services can gather large volumes of high-quality, customized text utterances or generate scenario-based responses to ensure your chatbots and conversational AI models are thoroughly trained for all conversation scenarios.

Speech and Audio Collection

Gather large volumes of high-quality, customized speech and audio data for training voice-prompted virtual assistants, voice activated search functions, voice-to-text capabilities and more. We provide data collection as a standalone service and as part of a multi-component deliverable such as an ASR speech database with audio data, transcription, pronunciation lexicons, and language-specific documents to ensure your ASR models sound flawless and natural in any locale you choose to launch in.

Trusted by global leaders to power their mission-critical AI with data for over 25 years

Annotation Capabilities

With a large range of data annotation capabilities built to serve many different industries, we are well-placed to serve a variety of project types.

Many of our annotation capabilities have Smart Labeling features which use machine learning assistance in the data annotation process to automate and improve productivity, quality, and delivery of your data collection and data annotation projects.

Text

Text Annotation (NER, POS)

Expand on your NLP labeling by connecting named entities or parts of speech within relationships so that your models form connections and greater understanding of textual content.

Text Classification (Sentiment, Intent, Content)

Increase chances of having a meaningful conversation by understanding intents behind customer queries and get insights from customer interactions.

Entity Extraction

Highlight and categorize relevant entities and train your model to derive key information from big volumes of text to improve the cognitive ability of your model.

Search Result Evaluation

Rank search results and improve user experience by using this data to train models to return the most relevant search results for the customer's query.

Text Evaluation and Post-Editing

Evaluate and improve the naturalness and relevance of the text generated by NLP models, such as machine translation models and other sequence models with the help of our multi-lingual specialists.

Audio

Audio Annotation

Segment audio into layers, speakers and timestamps for your Audio Speech Recognition and other audio models, training your models to accurately identify different speakers and other audio cues.

Audio Transcription

Leverage built-in NLP models to improve transcription quality and efficiency and transcribe spoken audio into text or validate machine-generated transcriptions. This process helps to accurately train Audio Speech Recognition models.

Audio Classification

Use sound categorization or utterance classification to classify audio based on language, dialect, semantics, and other features. This process helps train models to understand spoken cues.

Learn more about how we can help you with your next NLP project

Download Data Sheet

Trust

State-Of-The Art Data Privacy and Security

On-site secure data annotation and collection capabilities in Europe, US and Asia
Global work-from-home secure workspaces and single sign-on capabilities
Data privacy and security compliant, holding all major accreditations and certifications

Quality

High-Quality Results Delivered Consistently

Track record of delivering high-quality results at large scale for long-standing customers
Proven methodology and expertise to measure and delivery quality results
Reduced bias in results thanks to our globally representative workforce of over 1M in 170+ countries
Built-in features that monitor and improve quality during and after annotations

Usability

Easy to use Data for AI Lifecycle Platform

Variety of delivery models, ranging from self-service on our platform to fully outsourced
Intuitive Graphical User Interface with annotation job templates and 24/7 support
Powerful API integrations to connect into your existing MLOps infrastructure

Scale

Proven Ability to Scale Large Data Batches Across All Use Cases

Over 25 years of working with world’s largest and most innovative AI companies
Broad and deep data modality support
Over 1M crowd workers provide unmatched workforce diversity and scalability

Speed

High-Quality Training Data Accessible at Greater Speed

Pre-labeling powered by machine learning models to increase data annotation speed
Workflows to automate complex multistep tasks and sequential jobs

Linguistics

Build an AI product that aims to replicate and extend human communication (and delight users) by including linguists in the design, development and optimizing of AI for human interaction. As experts in natural communication, language behaviours and structures, linguists can help you to understand why users are behaving in this way – and what to do about it. Our services include:

Language Technology QA & Usability Testing
Dictionaries and Text Corpora
Localization Consulting
Linguistic Consulting

Learn More

Our purpose built text annotation tools make it easy to annotate text in detail, allowing your models to be trained to understand text and gain valuable insights.

Secure Data Access

Data security requirements are met for customers working with personally identifiable information (PII), protected health information (PHI), and other sophisticated compliance needs.

Enterprise-level security to protect sensitive client data

Secure Crowd

We offer a suite of secure service offerings with flexible options to ensure data security via secure facilities, secure remote workers, and onsite services to meet specific business needs.

Enterprise-level security to protect sensitive client data

Secure Facilities

We have sites in multiple geographies to support projects with Personally Identifiable Information (PII) and other sensitive data, as well as the right people, policies, and processes in place for a range of security levels, up to government level certification.

Enterprise-level security to protect sensitive client data

Secure Workspace

With our ISO 27001 accredited remote Secure Workspace solution, our global crowd can work on your sensitive projects remotely, without having to access a physical secure facility. This allows the diversity of our remote crowd to reduce bias and support multiple languages even through global disruptions.

Enterprise-level security to protect sensitive client data

Case Studies

CallMiner uses machine learning-powered audio training data to understand the sentiment of call center data and process more calls faster and with more accuracy, enabling them to explore new types of conversation insights with the extra time saved.

Read case study

Case Studies

The London School of Economics used globally sourced text training data to analyze political texts at scale to help create a model to identify political positions based on certain texts.

Read case study

Latest News and Resources

Blog

How the Human Element Balances AI and Contributor Efforts for Optimal Outcomes

Press Releases

Appen Launches AI Chat Feedback and Benchmarking Solutions for Enhanced LLM Evaluation

Blog

Appen's Benchmarking Solution: Confidently Choosing the Right LLM for Your Application

Blog

Appen's AI Chat Feedback Solution: Enhancing Conversational AI Performance

Blog

The White House’s Artificial Intelligence voluntary safety commitments missed the most essential component in the safeguarding of AI: human oversight.