阿里发布Qwen-Audio-3.0-ASR-Flash，强化上下文与领域术语识别

内部测试中，医疗术语召回率达95.36%，工业术语召回率达93.

24%。该模型支持自定义热词，并可将语音润色为结构化文本。

同步提供流式与文件转写两个版本。

Introducing Qwen-Audio-3.0-ASR-Flash: More context-aware. Stronger domain-term recognition. 🚀Our latest ASR model upgrades: • Context consistency • Domain-term recognition • Custom hotwords • Speech polishing into structured transcripts ⚡️In internal tests: • Medical term recall: 95.36% • Industrial term recall: 93.24% Qwen-Audio-3.0-ASR-Flash-Streaming： alibabacloud.com/help/en/model-… J Qwen-Audio-3.0-ASR-Flash-Filetrans: alibabacloud.com/help/en/model-… F Qwen-Audio-3.0-ASR-Flash: alibabacloud.com/help/en/model-… i📊 81 ⚡

This report is categorized under AITOP's "Models" desk, focusing on China's AI industry and domestic foundation model ecosystem. Within our cross-regional analytical framework, it directly maps to US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Qwen-Audio-3.0-ASR-Flash, 阿里云, 语音识别, 领域术语.

Source attribution: curated from 阿里通义 Qwen (@Alibaba_Qwen). Cross-source corroboration: 2 independent sources have covered this development (including IT之家), confirming industry-wide signal strength.