Tips on Choosing a Conversational AI Development Path
Blog post from Deepgram
Conversational AI, specifically voicebots, are transforming various industries. The process flow of a conversational AI voicebot involves audio capture, speech-to-text conversion, natural language processing and understanding (NLU/NLP), validation and business logic, response generation, and text-to-speech conversion. Key technologies involved include UCaaS, CCaaS, on-device applications, smart speakers, PBX, VOIP, speech-to-text platforms like Deepgram, Google STT, Amazon Transcribe, Nuance, and IBM Watson, NLU/NLP solutions such as OneReach.ai, Rasa, or Cognigy.ai, and text-to-speech providers like Agara.ai, Elerian.ai, and Uniphore. When choosing a development path for conversational AI, consider factors such as performance metrics, whether to build or buy the solution, communication platform approach (add on, all in one, or best of breed), and whether to opt for general or tailored solutions.
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