Automated speech recognition (ASR) has become a core technology for applications ranging from customer service call analysis to voice-controlled software. Developers and enterprise decision-makers have many speech-to-text APIs to choose from, each with different strengths. In this post, we’ll compare three of the most prominent solutions – Deepgram, AssemblyAI, and OpenAI’s Whisper – in detail. We’ll dive into transcription accuracy, language support, real-time transcription (streaming) capabilities, and advanced features like speaker diarization, sentiment analysis, and summarization. We’ll also evaluate the developer integration experience (API, SDKs, documentation) for each, and provide recommendations for various use cases (e.g. real-time transcription for customer service, batch audio transcription for recordings, accessibility tools, etc.).
Whether you’re searching for the best AI transcription service or doing a speech-to-text APIs comparison, this guide will help you understand the technical differences between Deepgram, AssemblyAI, and Whisper, and choose the right solution for your needs.
Transcription Accuracy
Deepgram uses end-to-end deep learning models optimized for real-world audio and offers specialized models (like Nova-3) that are fine-tuned for different audio types including phone calls and meetings. AssemblyAI's Universal-2 model is known for industry-leading accuracy with benchmarks showing over 93% transcription accuracy. Whisper, OpenAI's open-source model, is highly robust and approaches human-level transcription performance, particularly in English.
Language Support
Deepgram supports 30+ languages with automatic language detection. AssemblyAI supports 99+ languages and dialects, also with automatic detection. Whisper was trained on multilingual data across 95+ languages and includes language identification and translation capabilities.
Real-Time Capabilities
Deepgram and AssemblyAI support real-time transcription through WebSocket APIs. Deepgram achieves under 300ms latency, while AssemblyAI provides low-latency transcription (though currently limited to English for streaming). Whisper does not natively support streaming; while it can be adapted for it, latency is significantly higher.
Advanced Features
- Speaker Diarization: Deepgram and AssemblyAI support accurate diarization. Whisper requires external tools to add speaker labels.
- Sentiment Analysis: Only AssemblyAI offers this as a native feature.
- Summarization: AssemblyAI supports multiple summary formats; Deepgram mentions summarization but does not offer it natively in public APIs.
- PII Redaction: Both Deepgram and AssemblyAI offer PII redaction.
- Custom Vocabulary: Deepgram and AssemblyAI support keyword boosting. Whisper does not.
- Translation: Whisper can translate non-English speech into English. Deepgram and AssemblyAI focus on transcription.
Developer Experience and Integration
- Deepgram: Offers REST and WebSocket APIs, multiple SDKs (Python, Node.js, Java, etc.), excellent documentation, and on-prem deployment options.
- AssemblyAI: REST and streaming APIs, excellent SDK support, weekly product updates, rich documentation, and built-in post-processing features.
- Whisper: Open-source and flexible but requires more setup and compute resources. OpenAI offers a simple REST API but without real-time or advanced features.
Use Case Recommendations
Real-Time Customer Service Transcription & Analytics
- Best: Deepgram for low-latency and diarization.
- Also Consider: AssemblyAI for built-in sentiment and summarization (English-only streaming).
- Whisper: Viable for post-call analysis if integrated with external tools.
Batch Transcription of Recordings
- Best: AssemblyAI for multi-language support, summaries, and structured output.
- Deepgram: Ideal for high-speed batch processing and custom models.
- Whisper: Cost-effective and highly accurate for offline or privacy-focused workflows.
Accessibility Tools (Captions, Subtitles)
- Live Captions: Deepgram.
- Offline/Batch: AssemblyAI for summaries and structured formatting.
- On-device/Offline: Whisper for open-source control.
Compliance and Monitoring
- AssemblyAI: Content moderation, PII redaction, sentiment analysis.
- Deepgram: Fast search and redaction tools.
- Whisper: Open-source flexibility but requires custom integrations.
Translation and Multilingual
- Whisper: Best for multilingual translation and transcription.
- AssemblyAI: Broad language support.
- Deepgram: Strong performance for 30+ languages with more being added.
Summary of Key Differences
Transcription Accuracy:
- Deepgram: Excellent for real-world audio, custom models available.
- AssemblyAI: Leading accuracy on clean audio, strong formatting.
- Whisper: High general accuracy, best for open-source use.
Language Support:
- Deepgram: 30+ languages.
- AssemblyAI: 99+ languages.
- Whisper: ~95 languages with translation.
Streaming Support:
- Deepgram: Yes, ultra-low latency.
- AssemblyAI: Yes, English-only.
- Whisper: No native streaming.
Speaker Diarization:
- Deepgram: Yes.
- AssemblyAI: Yes.
- Whisper: No (external tool required).
Sentiment Analysis & Summarization:
- Deepgram: Limited or enterprise-only.
- AssemblyAI: Fully supported.
- Whisper: Not supported.
PII Redaction:
- Deepgram: Yes.
- AssemblyAI: Yes.
- Whisper: No.
Deployment Options:
- Deepgram: Cloud & On-Prem.
- AssemblyAI: Cloud only.
- Whisper: Open-source/on-prem supported.
Conclusion
Each of the three solutions offers compelling strengths:
- Choose Deepgram if you need real-time transcription, customization, or on-prem deployment.
- Choose AssemblyAI if you want built-in analytics, easy integration, and multi-language support.
- Choose Whisper if you need full control, on-device usage, or a cost-effective offline solution.
All three represent best-in-class speech recognition technologies. Your choice depends on specific needs like latency, privacy, analytics, and scale.