Speech-To-Text
AssemblyAI has become a widely-used speech AI platform, offering developers a comprehensive suite of tools for transcribing audio and extracting valuable insights. Its combination of accurate transcription, Audio Intelligence features like sentiment analysis and summarization, and the innovative LeMUR framework for applying large language models to voice data has made it a popular choice for companies building voice-enabled applications.
Speech-To-Text
When choosing a text-to-speech API (TTS), developers face crucial practical questions: Which provider delivers the right balance of latency, voice quality, control, and scalability in real production systems?
Speech-To-Text
Automatic speech recognition (ASR), aka speech-to-text (STT) technology, is a constantly evolving field. Knowing which ASR model is right for your product or service can be challenging. CTC, encoder-decoder, transducer, and speech LLMs—each with distinct tradeoffs. What does it all mean? And what do you choose?!
Speech-To-Text
Despite rapid advances in voice agent stacks, including speech-to-text (STT), text-to-speech (TTS), and large language models (LLMs), the real-world promise of fully autonomous voice assistants remains largely unmet.
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Speech-To-Text
Voice AI has taken a leap in 2025. From early IVR experiments that barely handled a “hello” to today’s real-time conversational agents running across industries, we've come a long way. But is it truly a solved issue?
Speech-To-Text
As voice agents become a core part of customer and employee experience, users need to know these AI systems are accurate, safe, and acting within boundaries. That’s especially true for enterprise-grade tools, where a rogue voice agent can severely damage relationships and create major legal risks.
