WeNet On-device ASR Android Demo
This Android demo shows we can run on-device streaming ASR with WeNet. You can download our prebuilt APK or build your APK from source code.
Prebuilt APK
- Chinese ASR Demo APK, with model trained on AIShell data
- English ASR Demo APK, with model trained on LibriSpeech data (To be added)
Build your APK from source code
1) Build model
You can use our pretrained model (click the following link to download):
- Chinese model trained on AIshell
- Model trained on AISHELL-2
- English model trained on LibriSpeech(TODO)
Or you can train your own model using WeNet training pipeline on your data.
2) Build APK
When your model is ready, put final.zip and words.txt into Android assets (app/src/main/assets) folder,
then just build and run the APK. Here is a gif demo, which shows how our on-device streaming e2e ASR runs with low latency.
Please note the wifi and data has been disabled in the demo so there is no network connection ^_^.
Compute the RTF
Step 1, connect your Android phone, and use adb push command to push your model, wav scp, and waves to the sdcard.
Step 2, build the binary and the APK with Android Studio directly, or with the commands as follows:
cd runtime/device/android/wenet
./gradlew build
Step 3, push your binary and the dynamic library to /data/local/tmp as follows:
adb push app/.cxx/cmake/release/arm64-v8a/decoder_main /data/local/tmp
adb push app/.cxx/cmake/release/arm64-v8a/gflags-build/lib/libgflags.so /data/local/tmp
adb push app/build/pytorch_android-1.6.0.aar/jni/arm64-v8a/* /data/local/tmp
Step 4, change to the directory /data/local/tmp of your phone, and export the library path by:
adb shell
cd /data/local/tmp
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:.
Step 5, execute the same command as the x86 demo to run the binary to decode and compute the RTF.