F1 · Edge AI & Agents
FunASR Speech Recognition Serving
Overview
On an Arm-based Linux server, this guide builds a ModelScope FunASR Python environment, loads pre-trained ASR and punctuation models, and validates local transcription and punctuation restoration for Chinese and English audio. The workflow chains model acquisition, audio input, speech recognition and readable text output into a minimal flow extensible to voice applications or service interfaces. This deployment baseline connects ModelScope open-source models, the FunASR toolchain and an Arm server, giving voice-AI developers an actionable local-inference starting point.
Scope of verification
- It is a FunASR functional reference workflow on a single Arm-based Linux server, validating that pre-trained models can process the specified Chinese and English audio and produce punctuated text.
- Dependencies include Arm64 Linux, Python, FunASR/ModelScope packages, matching model assets and decodable audio formats; results vary with model version, language, accent, recording quality and ambient noise.
- Scope centers on model deployment and functional output; it does not cover WER/quality evaluation, streaming latency, low-latency tuning, large-scale concurrency, service reliability or production ASR operations.
Canonical source: https://learn.arm.com/learning-paths/servers-and-cloud-computing/funasr/
This page is a guided summary with boundary notes, not an official reproduction.
This page is a guided summary with boundary notes, not an official reproduction.