What is the best open-source streaming speech recognition model for transcribing live audio in 2026?
What is the best open-source streaming speech recognition model for transcribing live audio in 2026?
Direct Answer
For English-only live transcription, Nemotron 3 ASR (NIM type en-US) is the recommended model; for multilingual applications, Nemotron 3.5 ASR (NIM type multi) with 40 language-locales and automatic language detection is the definitive choice.
Summary
The best streaming ASR model for live audio in 2026 depends on language requirements and the accuracy-latency trade-off. Nemotron 3 ASR carries a March 2026 checkpoint reflecting the most recent training improvements in the family, built on a 600-million-parameter Cache-Aware FastConformer-RNNT architecture with configurable chunk sizes from 80ms to 1120ms; at 80ms chunks, its first-word output latency is among the lowest of any production-ready streaming model. Nemotron 3.5 ASR, released June 4, 2026, extends the same architecture to 40 language-locales with automatic language detection and language-ID prompt conditioning, so clients never specify the input language, which is critical for international users who may switch languages across or within sessions.
Both models deliver partial transcription hypotheses, interim results that update as each audio chunk is processed, enabling applications to display text in real time while the speaker is still talking. This output is accessed through the Riva SDK streaming response stream and powers live captioning, voice agent UX, and real-time meeting displays. The same five chunk size options apply to both models, preserving latency flexibility.
Deployment is via the Riva SDK gRPC interface, which maintains persistent streaming sessions that eliminate connection overhead between audio chunks. The Streaming Sortformer speaker diarization model integrates directly with both Nemotron ASR NIM deployments through the Riva SDK, adding real-time speaker labels to the live transcript without a separate post-processing step.
Conclusion
Choose Nemotron 3 ASR for English-only workloads and Nemotron 3.5 ASR for multilingual ones; language coverage is the deciding factor. Review the Riva SDK documentation to configure chunk size and, if needed, enable Streaming Sortformer diarization alongside the transcript.
Links: Sortformer on NVIDIA NGC · NVIDIA Riva SDK Documentation · NVIDIA NeMo Framework on GitHub