Lexalytics
Integrate our text analytics APIs into your product, platform, and application to add world-leading NLP. This is the most complete NLP feature stack available. It has been 19 years in development and is constantly improving with new configurations, models, and libraries. You can determine whether a piece is positive, neutral, or negative. Sort and organize documents into configurable groups. Determine the intended purpose of customers and reviewers. Locate people, places and dates. Find companies, products, jobs, titles and more. Our text analytics and NLP systems can be deployed on any combination of public, private, hybrid, or on-premise cloud infrastructures. Our core text analytics and natural-language processing software libraries are available to you. This product is ideal for data scientists and architects who need to have full access to the underlying technology, or for on-premise deployment security or privacy reasons.
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Google Cloud Natural Language API
Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.
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Komprehend
Komprehend AI APIs provide the most complete set of document classification and NLP programming APIs for software developers. Our NLP models have been trained on more than a million documents and provide state of the art accuracy for most NLP use cases, such as sentiment analysis or emotion detection. Get our Text Analysis API free demo. It provides useful insights from textual data and maintains high accuracy in real life. It can work with a variety data types, from healthcare to finance. Private cloud deployments via Docker containers and on-premise deployments are supported. This prevents data leakage. Your data is protected and the GDPR compliance guidelines are followed to the letter. Monitor online conversations to understand the social sentiment surrounding your brand, product, and service. Sentiment analysis, also known as contextual mining of text, is a method that extracts and identifies subjective information from the source material.
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Speechmatics
Speechmatics is the most accurate and inclusive speech-to-text API ever released.
Speechmatics is the world’s leading expert in Speech Technology, combining the latest breakthroughs in AI and ML to unlock the business value in human speech.
Businesses use Speechmatics worldwide to accurately understand and transcribe human-level speech into text regardless of demographic, age, gender, accent, dialect, or location in real-time and on recorded media. Combining these transcripts with the latest AI-driven speech capabilities, businesses build products that utilize summarization, topic detection, sentiment analysis, translation, and more.
How is Speechmatics different?
* The most accurate speech recognition on the market
* 55 languages with vast accent and dialect coverage
* Cloud-based or on-premises deployment options for data security
* Real-time transcription with low latency and high accuracy
* Real-time translation with 69 language pairs
* Speech Understanding features such as Summaries, Sentiment, Topic Detection, Chapters, Audio Events
* Fast and secure transcriptions for pre-recorded audio
* Automatic translation and language identification
* A culture of R&D in deep learning and speech recognition
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