构建 sherpa-ncnn

官方提供的构建脚本需要在Linux/MacOS平台,选择的NDK版本22.1.7171670,由于我这里使用的是Window平台,所以直接使用预编译的库.

这里需要注意的是需要删除 Android NDK 中的硬编码调试标志以修复 android-ndk 问题

Demo构建

下载SherpaNcnnDemo代码

把我们下载的so库放置到jniLibs目录下

预训练模型选择

在Demo的注释中指示了哪些可用的预训练模型,可根据需要进行下载.下载解压后放置在assets目录下

/*
@param type
0 - https://huggingface.co/csukuangfj/sherpa-ncnn-2022-09-30
    This model supports only Chinese

1 - https://huggingface.co/csukuangfj/sherpa-ncnn-conv-emformer-transducer-2022-12-06
    This model supports both English and Chinese

2 - https://huggingface.co/csukuangfj/sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13
    This model supports both English and Chinese

3 - https://huggingface.co/csukuangfj/sherpa-ncnn-streaming-zipformer-en-2023-02-13
    This model supports only English

4 - https://huggingface.co/shaojieli/sherpa-ncnn-streaming-zipformer-fr-2023-04-14
    This model supports only French

5 - https://github.com/k2-fsa/sherpa-ncnn/releases/download/models/sherpa-ncnn-streaming-zipformer-zh-14M-2023-02-23.tar.bz2
    This is a small model and supports only Chinese
6 - https://github.com/k2-fsa/sherpa-ncnn/releases/download/models/sherpa-ncnn-streaming-zipformer-small-bilingual-zh-en-2023-02-16.tar.bz2
    This is a medium model and supports only Chinese

Please follow
https://k2-fsa.github.io/sherpa/ncnn/pretrained_models/index.html
to add more pre-trained models
 */
fun getModelConfig(type: Int, useGPU: Boolean): ModelConfig?

比如这里我选择使用sherpa-ncnn-conv-emformer-transducer-2022-12-06 这是一个中英双语支持的模型

至此项目应该就可以编译运行起来

参考链接

1. build-sherpa-ncnn
2. SherpaNcnnDemo代码