Data labeling for natural language processing
Extract information from natural language data and take full control of your training data. Power your NLP algorithm with datasets of any size.
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Annotations we support
With Toloka, you can control data labeling accuracy to build a predictable pipeline of high-quality training data that impacts your NLP algorithms. Our platform supports annotation for named entity recognition, sentiment analysis, speech recognition, text and intent classification, text recognition, and more.
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Search relevance
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Text classification
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Sentiment analysis
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Intent classification
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Utterance collection
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Named entity recognition
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Audio data collection
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Audio transcription
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Audio classification
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Text recognition
Use the Toloka crowd to evaluate the performance of your search engine and discover which ranking model works best. Collect data for improving your search relevance algorithm.
Price for 1000 tasks: $18. Turnaround time: 4 hours.*
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Ask Tolokers to classify or categorize entire texts with predefined category tags.
Price for 1000 tasks: $18.Turnaround time: 2 hours.*
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Use Toloka to label texts with sentiment categories for any purpose, from understanding customer reviews to spam filtering.
Price for 1000 tasks: $4.5. Turnaround time: 1 hour.*
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Ask Tolokers to categorize user queries into relevant predefined intents. Use labeled data to train your chatbot, voice assistant, or any other conversational agent to better understand your users.
Price for 100 tasks: $6. Turnaround time: 1 hour.*
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Create a collection of utterances that typically occur in conversations, based on instructions or scenarios that you provide for our Tolokers.
Price for 100 tasks: $12.Turnaround time: 4 hours.*
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Use our skilled Tolokers to identify parts of text, classify proper nouns, or label any other entities.
Price for 1000 tasks: $18. Turnaround time: 1 hour.*
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Get recorded speech samples from Tolokers according to your instructions and use them to create or fine-tune a voice interface.
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Ask Tolokers to transcribe audio files or check existing transcriptions for accuracy.
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Use Toloka to detect emotion, categorize topics, or identify events in audio samples or conversations to improve your model.
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Ask Tolokers to transcribe text in PDF files. Use labeled data to train your text recognition algorithms to better identify specific parts of scanned documents, or validate and fine-tune the output of your own OCR models.
Use cases:* Approximate cost. Not a public offer. Price and turnaround time for tasks are set by the requester and depend on the type of task, input data, and other factors.
Real-time insights
Track your projects with real-time statistics on progress, spending, quality, time spent on tasks and active users involved. Leverage detailed analytics to fine-tune as necessary and make timely decisions to optimize speed, quality and budget.
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