Merge whisper and parakeet into one app

.github/workflows/android-build.yml

@@ -36,11 +36,8 @@ jobs:
             path: mv3/android/MV3Demo
           - name: YoloDemo
             path: Yolo/android
-          - name: WhisperDemo
-            path: whisper/android/WhisperApp
-            require_aar: true
-          - name: ParakeetDemo
-            path: parakeet/android/ParakeetApp
+          - name: AsrDemo
+            path: asr/android/AsrApp
             require_aar: true
 
 
@@ -62,7 +59,7 @@ jobs:
         uses: gradle/actions/setup-gradle@v4
 
       - name: Download local AAR
-        if: ${{ inputs.local_aar && (matrix.name == 'LlamaDemo' || matrix.name == 'YoloDemo' || matrix.name == 'WhisperDemo' || matrix.name == 'ParakeetDemo') }}
+        if: ${{ inputs.local_aar && (matrix.name == 'LlamaDemo' || matrix.name == 'YoloDemo' || matrix.name == 'AsrDemo') }}
         run: |
           mkdir -p ${{ matrix.path }}/app/libs
           curl -fL -o ${{ matrix.path }}/app/libs/executorch.aar "${{ inputs.local_aar }}"
@@ -71,7 +68,7 @@ jobs:
         if: ${{ !matrix.require_aar || inputs.local_aar }}
         working-directory: ${{ matrix.path }}
         run: |
-          if [ -n "${{ inputs.local_aar }}" ] && ([ "${{ matrix.name }}" == "LlamaDemo" ] || [ "${{ matrix.name }}" == "YoloDemo" ] || [ "${{ matrix.name }}" == "WhisperDemo" ] || [ "${{ matrix.name }}" == "ParakeetDemo" ]); then
+          if [ -n "${{ inputs.local_aar }}" ] && ([ "${{ matrix.name }}" == "LlamaDemo" ] || [ "${{ matrix.name }}" == "YoloDemo" ] || [ "${{ matrix.name }}" == "AsrDemo" ]); then
             ./gradlew build --no-daemon -PuseLocalAar=true
           else
             ./gradlew build --no-daemon

asr/android/AsrApp/README.md

@@ -0,0 +1,37 @@
+# ASR Demo App
+
+This app demonstrates running speech recognition models on Android using ExecuTorch. It supports both **Whisper** and **Parakeet** model families.
+
+## Supported Models
+
+| Model | Type | Details |
+|-------|------|---------|
+| Whisper Tiny/Small/Medium (INT8/INT4) | Streaming | Requires model, tokenizer, and preprocessor |
+| Whisper Tiny/Small/Medium (FP32) | Streaming | Requires model, tokenizer, and preprocessor |
+| Parakeet TDT 0.6B (INT4) | Synchronous | Requires model and tokenizer |
+
+## Export Model Files
+
+- **Whisper**: Follow the instructions at https://github.com/pytorch/executorch/tree/main/examples/models/whisper
+- **Parakeet**: Follow the instructions at https://github.com/pytorch/executorch/tree/main/examples/models/parakeet
+
+## Run the App
+
+1. Open AsrApp in Android Studio
+2. Copy the `executorch.aar` library (with ASR and Parakeet JNI bindings) into `app/libs/`
+3. Build and run on device
+
+## Download Models
+
+The app includes a built-in download screen to fetch models from HuggingFace. Alternatively, push files manually:
+
+```bash
+adb push model.pte /data/local/tmp/asr/
+adb push tokenizer.json /data/local/tmp/asr/
+adb push whisper_preprocessor.pte /data/local/tmp/asr/  # Whisper only
+```
+
+## Recording Behavior
+
+- **Whisper**: Click to start recording; automatically stops after 30 seconds
+- **Parakeet**: Click to start recording; click again to stop (no time limit)

whisper/android/WhisperApp/app/build.gradle.kts → asr/android/AsrApp/app/build.gradle.kts

@@ -7,11 +7,11 @@ plugins {
 val useLocalAar: Boolean? = (project.findProperty("useLocalAar") as? String)?.toBoolean()
 
 android {
-    namespace = "com.example.whisperapp"
+    namespace = "com.example.asrapp"
     compileSdk = 35
 
     defaultConfig {
-        applicationId = "com.example.whisperapp"
+        applicationId = "com.example.asrapp"
         minSdk = 24
         targetSdk = 35
         versionCode = 1
@@ -56,4 +56,4 @@ dependencies {
         implementation("org.pytorch:executorch-android:1.1.0")
     }
     implementation("com.facebook.fbjni:fbjni:0.5.1")
-}
+}