Speech-to-Text API

AssemblyAI's Speech-to-Text API is a cloud-based service that converts audio into text with a focus on 'Speech Understanding'—transcription combined with built-in analysis features such as speaker diarization, sentiment analysis, content summarization, topic and entity detection, and content moderation. It is designed for developers and enterprises building applications that require more than raw transcription, including contact centers, medical transcription workflows, voice agents, and conversation intelligence platforms. The API supports both batch processing and real-time streaming, with sub-300ms latency for live use cases, and accepts a wide range of file formats including MP3, MP4, WAV, and FLAC. AssemblyAI targets teams that need production-ready accuracy and a growing feature set without stitching together multiple third-party services.

The API operates on a per-second billing model for batch processing, avoiding the overhead of per-minute or block-based rounding that can inflate costs by 30-40% for short audio clips. Its flagship model, Universal-3 Pro, achieves a 4.97% mean error rate (MER) on medical terminology when used with the Medical Mode add-on, compared to Deepgram's Nova-3 Medical at 7.32% MER. For a one-hour audio file, AssemblyAI processes batch transcription in about 35 seconds, while streaming transcription costs $0.45 per hour versus $0.21 per hour for batch. The platform includes an LLM Gateway for downstream analysis, automatic PII redaction, and word-level speaker identification, all bundled into a single API call rather than charged as separate add-ons.

AssemblyAI competes directly with Google Cloud Speech-to-Text and Deepgram, positioning itself as a middle ground between raw transcription and full analysis. Google Cloud offers 60 minutes of free transcription plus $300 in cloud credits for new users, but its feature set is less integrated, requiring separate services for sentiment or entity extraction. Deepgram prioritizes ultra-fast processing (around 90 seconds for one hour of audio) but lacks built-in analysis features like sentiment, summarization, or content moderation, forcing users to build custom pipelines. AssemblyAI differentiates with its bundled Speech Understanding features, which reduce integration complexity and total cost of ownership for applications that need both transcription and insight extraction.

The honest trade-offs: AssemblyAI's pricing can become complex at scale due to feature-specific costs (e.g., Medical Mode, LLM Gateway), and its streaming rates are more than double batch rates, which may surprise users with real-time needs. While accuracy is enterprise-grade for general and medical use, some dedicated providers may edge it out on niche tasks like heavy noise robustness or non-native accents. The platform's rapid feature expansion means documentation occasionally lags behind new releases, and its focus on cloud-only deployment limits options for air-gapped environments. For teams that prioritize speed over analysis, Deepgram's simpler pricing and faster processing may be a better fit, while Google Cloud appeals to those already in the Google ecosystem.

Free tier includes $50 in credits, enough for hundreds of hours of audio. Batch transcription with Universal-3 Pro costs $0.21 per hour; streaming costs $0.45 per hour. Feature add-ons (Medical Mode, LLM Gateway) incur additional per-hour charges. No fixed tier names published; usage-based scaling.