Cactus Whistle 对比 Whisper Base：16.9 MB 语音模型在 CPU 上的实测教程
A Coding Guide to Cactus Whistle: Does a 16.9 MB Speech Model Hold Up Against Whisper Base? Word Error Rate, Speed, Streaming, Timestamps, Keywords, and Speech-to-Tool Calls on a CPU
教你怎么在 CPU 上跑 Cactus Whistle 这个 16.9 MB 的语音识别小模型，还把它和 Whisper base 比了词错率和速度，想做端侧语音的可以直接抄代码。
MarkTechPost 发布一篇编码教程，用 Cactus Compute 的 16.9 MB 语音模型与 Whisper base 在 CPU 上做对比。评测指标包括词错率（WER）、推理速度、流式延迟、时间戳、关键词识别和语音转工具调用。文章给出了完整代码，展示该小模型在端侧场景的实际表现。
A Coding Guide to Cactus Whistle: Does a 16.9 MB Speech Model Hold Up Against Whisper Base? Word Error Rate, Speed, Streaming, Timestamps, Keywords, and Speech-to-Tool Calls on a CPU
Explore a comprehensive coding guide benchmarking Cactus Compute's 16.9 MB speech model against Whisper base. Learn about word error rates, CPU speed, streaming latency, and speech-to-tool integration. The post A Coding Guide to Cactus Whistle: Does a 16.9 MB Speech Model Hold Up Against Whisper Base? Word Error Rate, Speed, Streaming, Timestamps, Keywords, and Speech-to-Tool Calls on a CPU appeared first on MarkTechPost .
