Speech Recognition in AI: A Beginner's Guide
Blog post from Deepgram
The guide provides an in-depth overview of speech recognition in AI, emphasizing the differences between speech and voice recognition and outlining the core outputs of ASR APIs, such as transcripts, timestamps, and confidence scores. It discusses real-time and batch transcription modes, the AI pipeline's conversion of voice to text, and the superiority of modern transformer-based models over legacy systems. It also highlights real-world challenges like accents, background noise, and domain-specific vocabulary that can impact accuracy, and offers advice on selecting suitable APIs based on accuracy, latency, pricing, and deployment options. The guide suggests starting with batch transcription for initial integration, moving to streaming, and eventually adding audio intelligence features if needed. It stresses the importance of testing with real-world audio to ensure production readiness and addresses the cost implications of deploying speech recognition technology.