NeuralSpace Reviews

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

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.