AI call analytics platforms vs. STT APIs: which is right for multilingual transcription?
Blog post from Gladia
The text explores the complexities and considerations involved in selecting between AI call analytics platforms and Speech-to-Text (STT) APIs for multilingual transcription at scale, focusing on factors such as language coverage, code-switching, accent handling, and pricing structures. It highlights the challenges of relying solely on English benchmarks when scaling to multilingual markets and the importance of testing models on specific languages and accents relevant to a company's operations. Gladia's Solaria models are emphasized for their breadth and depth in language support, with Solaria-1 covering over 100 languages with real-time code-switching capabilities, making it suitable for diverse global markets. The text also discusses the economic implications of different pricing models, where some platforms charge separately for features like diarization and sentiment analysis, while Gladia's plans bundle these at a base rate. It underscores the importance of evaluating WER (Word Error Rate) in real-world conditions and ensuring accuracy for diverse accents and specific industry jargon, recommending teams to conduct tests with their own production recordings to make informed decisions.
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