Tool overview
Overview
Mynah ASR is a native C inference engine for speech recognition and translation. It is designed in the style of llama.cpp and whisper.cpp, providing streaming and offline capabilities, with support for CPU, Metal, and CUDA backends, and no Python runtime dependency. It runs open speech models such as Parakeet, Canary, and Nemotron, and the engine layer is model-agnostic. The engine is written in pure C11 with zero runtime dependencies, including its own f32 GEMM. It supports 10 models across four decoder families: RNNT, TDT, CTC, and AED (Canary). It offers speech translation via Canary models, with CLI and server endpoints. It includes cache-aware streaming with selectable latency, per-word timestamps, automatic segmentation, and an OpenAI-compatible REST and WebSocket server. Additional
features
include 40 languages with language detection (Nemotron) and 25 EU languages with punctuation and inverse text normalization (Parakeet v3, canary-1b-v2). It includes Silero VAD ported to C, two weight containers (safetensors and GGUF), and lightweight Python and Node bindings. Quality is measured on real audio with CER 0.00–0.07 across 11 languages.
Features
- AI assistant
- Natural language interface
- Workflow automation
Tags
Use Cases
Teams use Mynah ASR to transcribe audio files offline with automatic resampling.
Teams use Mynah ASR to perform live streaming transcription from a microphone or pipe.
Teams use Mynah ASR to translate speech between languages.
Teams use Mynah ASR to detect the language of unknown audio.
Teams use Mynah ASR to generate per-word timestamps.
Teams use Mynah ASR to segment long audio files automatically.
Teams use Mynah ASR to deploy an OpenAI-compatible REST and WebSocket server.
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