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[WIP] Fetch upstream #6
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If the input audio file is less than 10 seconds long, there is only one chunk, and there is no need to compute embeddings or do clustering. We can use the segmentation result from the speaker segmentation model directly.
#1408 uses [node-addon-api](https://github.com/nodejs/node-addon-api) to call C API from JavaScript, whereas this pull request uses WebAssembly to call C API from JavaScript.
It is contributed by a community user from [our QQ group](https://k2-fsa.github.io/sherpa/social-groups.html#qq).
… be found for specific aarch64 cross-compilation environments (#1436) Co-authored-by: xiao <shawl336@163.com>
--------- Co-authored-by: root <1552138571@qq.com>
It is a wrapper around the C API.
…1699) 由于SenseVoiceSmall.from_pretrained() 调用的funasr.auto.auto_model.AutoModel.build_model()默认device是cuda (在cuda available的环境中) ```py device = kwargs.get("device", "cuda") if not torch.cuda.is_available() or kwargs.get("ngpu", 1) == 0: device = "cpu" kwargs["batch_size"] = 1 kwargs["device"] = device ``` 而export-onnx.py里的tensor默认都是cpu, 导致 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu 所以直接在加载model的时候指定cpu
See also #1695 (comment) We need to place a 0 at the end of the buffer.
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