StressLess Android Application Architecture

Using SpeechBrain ECAPA-TDNN as Primary Engine

Executive Summary

This document presents a comprehensive Android application architecture for StressLess, leveraging SpeechBrain ECAPA-TDNN as the primary voice analysis engine. The architecture emphasizes NPU acceleration, offline-first operation, and privacy-by-design principles while delivering sub-3-second stress analysis performance.

Core Architecture Overview

High-Level System Design

Layer 1: Presentation Layer (Jetpack Compose)

Core UI Components

1. Voice Recording Interface

@Composable
fun VoiceRecordingScreen(
    viewModel: StressAnalysisViewModel = hiltViewModel()
) {
    val uiState by viewModel.uiState.collectAsState()
    val context = LocalContext.current
    
    Column(
        modifier = Modifier.fillMaxSize(),
        horizontalAlignment = Alignment.CenterHorizontally
    ) {
        // Real-time voice visualization
        VoiceVisualizationCard(
            isRecording = uiState.isRecording,
            audioLevel = uiState.currentAudioLevel,
            modifier = Modifier
                .fillMaxWidth()
                .height(200.dp)
                .padding(16.dp)
        )
        
        // NPU status indicator
        NPUStatusIndicator(
            isNPUAvailable = uiState.isNPUAvailable,
            processingMode = uiState.processingMode
        )
        
        // Recording controls
        RecordingControlButton(
            isRecording = uiState.isRecording,
            onClick = { 
                if (uiState.isRecording) {
                    viewModel.stopRecording()
                } else {
                    viewModel.startRecording()
                }
            },
            modifier = Modifier
                .size(120.dp)
                .padding(24.dp)
        )
        
        // Analysis progress
        if (uiState.isAnalyzing) {
            StressAnalysisProgress(
                progress = uiState.analysisProgress,
                estimatedTimeRemaining = uiState.estimatedTime
            )
        }
        
        // Results display
        uiState.stressResult?.let { result ->
            StressResultCard(
                stressLevel = result.level,
                confidence = result.confidence,
                recommendations = result.recommendations,
                processingTime = result.processingTimeMs
            )
        }
    }
}

2. Real-time Stress Dashboard

@Composable
fun StressDashboard(
    viewModel: DashboardViewModel = hiltViewModel()
) {
    val stressData by viewModel.stressData.collectAsState()
    val insights by viewModel.aiInsights.collectAsState()
    
    LazyColumn {
        item {
            // Current stress status
            CurrentStressCard(
                currentLevel = stressData.currentStressLevel,
                trend = stressData.trend,
                lastAssessment = stressData.lastAssessmentTime
            )
        }
        
        item {
            // Weekly stress pattern chart
            StressPatternChart(
                data = stressData.weeklyPattern,
                modifier = Modifier
                    .fillMaxWidth()
                    .height(200.dp)
                    .padding(16.dp)
            )
        }
        
        item {
            // AI-powered insights from Gemma-3n
            if (insights.isNotEmpty()) {
                AIInsightsCard(
                    insights = insights,
                    onInsightClick = viewModel::onInsightClicked
                )
            }
        }
        
        item {
            // Privacy status indicator
            PrivacyStatusCard(
                dataProcessedLocally = stressData.localProcessingCount,
                dataSharedCount = stressData.sharedDataCount
            )
        }
    }
}

@Composable
fun PrivacySettingsScreen(
    viewModel: PrivacyViewModel = hiltViewModel()
) {
    val privacyState by viewModel.privacyState.collectAsState()
    
    Column(
        modifier = Modifier
            .fillMaxSize()
            .padding(16.dp)
    ) {
        // GDPR consent management
        GDPRConsentSection(
            consentStatus = privacyState.consentStatus,
            onConsentChange = viewModel::updateConsent
        )
        
        // Data processing transparency
        DataProcessingCard(
            localProcessingEnabled = privacyState.localProcessingOnly,
            dataRetentionDays = privacyState.dataRetentionDays,
            onSettingChange = viewModel::updateDataSettings
        )
        
        // Export personal data (GDPR Article 15)
        ExportDataSection(
            onExportRequest = viewModel::requestDataExport,
            exportStatus = privacyState.exportStatus
        )
        
        // Delete all data (GDPR Article 17)
        DeleteDataSection(
            onDeleteRequest = viewModel::requestDataDeletion,
            deletionStatus = privacyState.deletionStatus
        )
    }
}

Layer 2: Business Logic Layer

Stress Analysis Manager (Orchestrator)

@Singleton
class StressAnalysisManager @Inject constructor(
    private val ecapaEngine: ECAPAStressEngine,
    private val audioProcessor: AudioProcessingPipeline,
    private val privacyController: PrivacyController,
    private val wellnessEngine: WellnessRecommendationEngine,
    private val localRepository: LocalStressRepository
) {
    
    suspend fun performStressAnalysis(
        audioData: ByteArray,
        context: StressAnalysisContext
    ): StressAnalysisResult = withContext(Dispatchers.Default) {
        
        // 1. Privacy compliance check
        privacyController.validateAnalysisPermissions(context)
        
        // 2. Audio preprocessing
        val processedAudio = audioProcessor.preprocessAudio(audioData)
        
        // 3. Feature extraction
        val features = audioProcessor.extractMFCCFeatures(processedAudio)
        
        // 4. ECAPA-TDNN stress analysis (NPU accelerated)
        val stressEmbeddings = ecapaEngine.extractStressEmbeddings(features)
        val stressLevel = ecapaEngine.classifyStress(stressEmbeddings)
        
        // 5. Generate wellness recommendations
        val recommendations = wellnessEngine.generateRecommendations(
            stressLevel = stressLevel,
            context = context,
            historicalData = localRepository.getRecentAssessments()
        )
        
        // 6. Store results locally (encrypted)
        val result = StressAnalysisResult(
            level = stressLevel.level,
            confidence = stressLevel.confidence,
            embeddings = stressEmbeddings,
            recommendations = recommendations,
            timestamp = System.currentTimeMillis(),
            processingTimeMs = measureProcessingTime()
        )
        
        localRepository.saveStressAssessment(result)
        
        return@withContext result
    }
    
    private fun measureProcessingTime(): Long {
        // Track performance metrics for NPU optimization
        return System.currentTimeMillis() - analysisStartTime
    }
}

Audio Processing Pipeline

@Singleton
class AudioProcessingPipeline @Inject constructor(
    private val bufferPool: AudioBufferPool,
    private val featureExtractor: AudioFeatureExtractor
) {
    
    private val audioFormat = AudioFormat.Builder()
        .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
        .setSampleRate(16000) // Optimized for ECAPA-TDNN
        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
        .build()
    
    fun preprocessAudio(rawAudioData: ByteArray): FloatArray {
        val buffer = bufferPool.acquire() ?: FloatArray(16000) // 1 second at 16kHz
        
        try {
            // Convert byte array to float array
            val audioSamples = convertBytesToFloat(rawAudioData)
            
            // Apply audio preprocessing
            val processedAudio = applyPreprocessing(audioSamples)
            
            return processedAudio
        } finally {
            bufferPool.release(buffer)
        }
    }
    
    suspend fun extractMFCCFeatures(audioData: FloatArray): FloatArray = 
        withContext(Dispatchers.Default) {
            featureExtractor.extractMFCC(
                audioData = audioData,
                sampleRate = 16000,
                numMFCC = 39, // Optimized for ECAPA-TDNN
                frameLength = 400, // 25ms frames
                hopLength = 160   // 10ms hop
            )
        }
    
    private fun applyPreprocessing(audio: FloatArray): FloatArray {
        return audio
            .let { removeNoiseProfile(it) }
            .let { normalizeAudio(it) }
            .let { applyHighPassFilter(it) }
    }
}

Layer 3: AI/ML Processing Layer

ECAPA-TDNN Engine (Primary)

@Singleton
class ECAPAStressEngine @Inject constructor(
    private val npuDelegate: NPUDelegate,
    private val modelCache: ModelCache,
    private val performanceMonitor: PerformanceMonitor
) {
    
    private var ecapaInterpreter: Interpreter? = null
    private var stressClassifier: Interpreter? = null
    
    suspend fun initialize() = withContext(Dispatchers.IO) {
        try {
            // Load SpeechBrain ECAPA-TDNN model
            val ecapaModel = modelCache.loadModel("speechbrain-ecapa-voxceleb.tflite")
            val classifierModel = modelCache.loadModel("stress-classifier.tflite")
            
            // Initialize with NPU delegation
            val options = Interpreter.Options().apply {
                if (npuDelegate.isNPUAvailable()) {
                    addDelegate(npuDelegate.createDelegate())
                    setNumThreads(1) // NPU handles parallelism
                } else {
                    setNumThreads(4) // Fallback to CPU
                    setUseXNNPACK(true) // CPU optimization
                }
            }
            
            ecapaInterpreter = Interpreter(ecapaModel, options)
            stressClassifier = Interpreter(classifierModel, options)
            
            Log.i("ECAPA", "Initialized with ${if (npuDelegate.isNPUAvailable()) "NPU" else "CPU"}")
            
        } catch (e: Exception) {
            Log.e("ECAPA", "Initialization failed", e)
            initializeFallback()
        }
    }
    
    suspend fun extractStressEmbeddings(mfccFeatures: FloatArray): FloatArray = 
        withContext(Dispatchers.Default) {
            performanceMonitor.startTiming("ecapa_embedding_extraction")
            
            try {
                // Prepare input tensor
                val inputBuffer = ByteBuffer.allocateDirect(mfccFeatures.size * 4)
                    .order(ByteOrder.nativeOrder())
                    .asFloatBuffer()
                    .put(mfccFeatures)
                
                // Prepare output tensor (192-dimensional ECAPA embeddings)
                val outputBuffer = ByteBuffer.allocateDirect(192 * 4)
                    .order(ByteOrder.nativeOrder())
                
                // Run ECAPA-TDNN inference
                ecapaInterpreter?.run(inputBuffer, outputBuffer)
                
                // Extract embeddings
                val embeddings = FloatArray(192)
                outputBuffer.rewind()
                outputBuffer.asFloatBuffer().get(embeddings)
                
                performanceMonitor.endTiming("ecapa_embedding_extraction")
                
                return@withContext embeddings
                
            } catch (e: Exception) {
                Log.e("ECAPA", "Embedding extraction failed", e)
                throw StressAnalysisException("ECAPA embedding extraction failed", e)
            }
        }
    
    suspend fun classifyStress(embeddings: FloatArray): StressClassification = 
        withContext(Dispatchers.Default) {
            performanceMonitor.startTiming("stress_classification")
            
            try {
                // Prepare input (ECAPA embeddings)
                val inputBuffer = ByteBuffer.allocateDirect(embeddings.size * 4)
                    .order(ByteOrder.nativeOrder())
                    .asFloatBuffer()
                    .put(embeddings)
                
                // Prepare output (10 stress levels)
                val outputBuffer = ByteBuffer.allocateDirect(10 * 4)
                    .order(ByteOrder.nativeOrder())
                
                // Run stress classification
                stressClassifier?.run(inputBuffer, outputBuffer)
                
                // Parse results
                val probabilities = FloatArray(10)
                outputBuffer.rewind()
                outputBuffer.asFloatBuffer().get(probabilities)
                
                val predictedLevel = probabilities.indices.maxByOrNull { 
                    probabilities[it] 
                }?.plus(1) ?: 1
                
                val confidence = probabilities.maxOrNull() ?: 0f
                
                performanceMonitor.endTiming("stress_classification")
                
                return@withContext StressClassification(
                    level = predictedLevel,
                    confidence = confidence,
                    probabilities = probabilities
                )
                
            } catch (e: Exception) {
                Log.e("ECAPA", "Stress classification failed", e)
                throw StressAnalysisException("Stress classification failed", e)
            }
        }
}

NPU Hardware Abstraction Layer

@Singleton
class NPUDelegate @Inject constructor(
    private val deviceInfoProvider: DeviceInfoProvider
) {
    
    private var npuType: NPUType = NPUType.NONE
    private var delegate: Delegate? = null
    
    enum class NPUType {
        QUALCOMM_HEXAGON,
        MEDIATEK_APU,
        SAMSUNG_NPU,
        GOOGLE_TENSOR,
        NONE
    }
    
    fun initialize() {
        npuType = detectNPUType()
        delegate = createNPUDelegate()
    }
    
    private fun detectNPUType(): NPUType {
        val deviceModel = Build.MODEL.lowercase()
        val chipset = deviceInfoProvider.getChipsetInfo()
        
        return when {
            chipset.contains("snapdragon", ignoreCase = true) -> {
                Log.i("NPU", "Detected Qualcomm Snapdragon NPU")
                NPUType.QUALCOMM_HEXAGON
            }
            chipset.contains("dimensity", ignoreCase = true) -> {
                Log.i("NPU", "Detected MediaTek APU")
                NPUType.MEDIATEK_APU
            }
            chipset.contains("exynos", ignoreCase = true) -> {
                Log.i("NPU", "Detected Samsung NPU")
                NPUType.SAMSUNG_NPU
            }
            chipset.contains("tensor", ignoreCase = true) -> {
                Log.i("NPU", "Detected Google Tensor TPU")
                NPUType.GOOGLE_TENSOR
            }
            else -> {
                Log.i("NPU", "No NPU detected, using CPU/GPU fallback")
                NPUType.NONE
            }
        }
    }
    
    fun createDelegate(): Delegate? {
        return when (npuType) {
            NPUType.QUALCOMM_HEXAGON -> {
                try {
                    // Qualcomm AI Engine Direct delegate
                    val options = QnnDelegate.Options().apply {
                        setBackendType(QnnDelegate.Options.BackendType.HTP_BACKEND)
                        setPerformanceMode(QnnDelegate.Options.PerformanceMode.HIGH_PERFORMANCE)
                        setPrecisionMode(QnnDelegate.Options.PrecisionMode.FP16)
                    }
                    QnnDelegate(options)
                } catch (e: Exception) {
                    Log.w("NPU", "Qualcomm NPU delegate creation failed", e)
                    createGPUFallback()
                }
            }
            NPUType.MEDIATEK_APU -> {
                try {
                    // MediaTek NeuroPilot delegate (when available)
                    NeuronDelegate(NeuronDelegate.Options())
                } catch (e: Exception) {
                    Log.w("NPU", "MediaTek NPU delegate creation failed", e)
                    createGPUFallback()
                }
            }
            else -> createGPUFallback()
        }
    }
    
    private fun createGPUFallback(): Delegate {
        return GpuDelegate(GpuDelegate.Options().apply {
            setInferencePreference(GpuDelegate.Options.INFERENCE_PREFERENCE_FAST_SINGLE_ANSWER)
            setPrecisionLossAllowed(true) // Allow FP16 for performance
        })
    }
    
    fun isNPUAvailable(): Boolean = npuType != NPUType.NONE && delegate != null
    
    fun getPerformanceInfo(): NPUPerformanceInfo {
        return NPUPerformanceInfo(
            npuType = npuType,
            isAvailable = isNPUAvailable(),
            estimatedTOPS = getEstimatedTOPS(),
            supportedPrecision = getSupportedPrecision()
        )
    }
}

Layer 4: Data Layer

Encrypted Local Storage

@Singleton
class LocalStressRepository @Inject constructor(
    private val database: StressLessDatabase,
    private val encryptionManager: EncryptionManager,
    private val privacyController: PrivacyController
) {
    
    suspend fun saveStressAssessment(assessment: StressAnalysisResult) = 
        withContext(Dispatchers.IO) {
            // Encrypt sensitive data before storage
            val encryptedEmbeddings = encryptionManager.encrypt(
                assessment.embeddings.joinToString(",")
            )
            
            val encryptedRecommendations = encryptionManager.encrypt(
                assessment.recommendations.joinToString("|")
            )
            
            val entity = StressAssessmentEntity(
                id = generateUUID(),
                stressLevel = assessment.level,
                confidence = assessment.confidence,
                encryptedEmbeddings = encryptedEmbeddings,
                encryptedRecommendations = encryptedRecommendations,
                timestamp = assessment.timestamp,
                processingTimeMs = assessment.processingTimeMs,
                synced = false
            )
            
            database.stressAssessmentDao().insertAssessment(entity)
            
            // Update privacy audit log
            privacyController.logDataProcessing(
                operation = "STRESS_ASSESSMENT_STORED",
                dataType = "VOICE_ANALYSIS_RESULT",
                processingBasis = "LEGITIMATE_INTEREST"
            )
        }
    
    suspend fun getStressHistory(
        startDate: Long,
        endDate: Long
    ): List<StressAnalysisResult> = withContext(Dispatchers.IO) {
        val entities = database.stressAssessmentDao()
            .getAssessmentsByDateRange(startDate, endDate)
        
        entities.map { entity ->
            val embeddings = encryptionManager.decrypt(entity.encryptedEmbeddings)
                .split(",")
                .map { it.toFloat() }
                .toFloatArray()
            
            val recommendations = encryptionManager.decrypt(entity.encryptedRecommendations)
                .split("|")
            
            StressAnalysisResult(
                level = entity.stressLevel,
                confidence = entity.confidence,
                embeddings = embeddings,
                recommendations = recommendations,
                timestamp = entity.timestamp,
                processingTimeMs = entity.processingTimeMs
            )
        }
    }
    
    suspend fun exportAllData(): String = withContext(Dispatchers.IO) {
        // GDPR Article 15 - Right of access
        val allAssessments = database.stressAssessmentDao().getAllAssessments()
        val exportData = PersonalDataExport(
            assessments = allAssessments,
            privacyLog = privacyController.getPrivacyAuditLog(),
            consentHistory = privacyController.getConsentHistory(),
            exportTimestamp = System.currentTimeMillis()
        )
        
        Json.encodeToString(exportData)
    }
    
    suspend fun deleteAllData() = withContext(Dispatchers.IO) {
        // GDPR Article 17 - Right to erasure
        database.clearAllTables()
        encryptionManager.destroyAllKeys()
        privacyController.logDataDeletion("USER_REQUESTED_DELETION")
    }
}

Model Management System

@Singleton
class ModelCache @Inject constructor(
    private val context: Context,
    private val encryptionManager: EncryptionManager
) {
    
    private val modelCache = mutableMapOf<String, ByteBuffer>()
    
    suspend fun loadModel(modelName: String): ByteBuffer = withContext(Dispatchers.IO) {
        // Check cache first
        modelCache[modelName]?.let { return@withContext it }
        
        // Load from assets
        val modelBuffer = when (modelName) {
            "speechbrain-ecapa-voxceleb.tflite" -> {
                loadAssetModel("models/speechbrain_ecapa_voxceleb_quantized.tflite")
            }
            "stress-classifier.tflite" -> {
                loadAssetModel("models/stress_classifier_quantized.tflite")
            }
            "gemma-3n-e2b.tflite" -> {
                loadAssetModel("models/gemma_3n_e2b_quantized.tflite")
            }
            else -> throw IllegalArgumentException("Unknown model: $modelName")
        }
        
        // Cache model for future use
        modelCache[modelName] = modelBuffer
        
        Log.i("ModelCache", "Loaded model: $modelName (${modelBuffer.capacity()} bytes)")
        
        return@withContext modelBuffer
    }
    
    private fun loadAssetModel(assetPath: String): ByteBuffer {
        context.assets.open(assetPath).use { inputStream ->
            val modelBytes = inputStream.readBytes()
            
            // Verify model integrity
            val checksum = calculateMD5(modelBytes)
            verifyModelChecksum(assetPath, checksum)
            
            return ByteBuffer.allocateDirect(modelBytes.size).apply {
                put(modelBytes)
                rewind()
            }
        }
    }
    
    fun preloadModels() {
        // Background preloading of critical models
        GlobalScope.launch(Dispatchers.IO) {
            try {
                loadModel("speechbrain-ecapa-voxceleb.tflite")
                loadModel("stress-classifier.tflite")
                Log.i("ModelCache", "Critical models preloaded successfully")
            } catch (e: Exception) {
                Log.e("ModelCache", "Model preloading failed", e)
            }
        }
    }
}

Dependency Injection Setup (Hilt)

Application Module

@Module
@InstallIn(SingletonComponent::class)
object StressLessAppModule {
    
    @Provides
    @Singleton
    fun provideStressLessDatabase(@ApplicationContext context: Context): StressLessDatabase {
        // SQLCipher encrypted database
        val passphrase = SQLiteDatabase.getBytes("secure_passphrase".toCharArray())
        
        return Room.databaseBuilder(
            context,
            StressLessDatabase::class.java,
            "stressless_encrypted.db"
        )
        .openHelperFactory(SupportFactory(passphrase))
        .fallbackToDestructiveMigration()
        .build()
    }
    
    @Provides
    @Singleton
    fun provideECAPAStressEngine(
        npuDelegate: NPUDelegate,
        modelCache: ModelCache,
        performanceMonitor: PerformanceMonitor
    ): ECAPAStressEngine {
        return ECAPAStressEngine(npuDelegate, modelCache, performanceMonitor)
    }
    
    @Provides
    @Singleton
    fun provideNPUDelegate(deviceInfoProvider: DeviceInfoProvider): NPUDelegate {
        return NPUDelegate(deviceInfoProvider).apply { initialize() }
    }
    
    @Provides
    @Singleton
    fun provideAudioProcessingPipeline(
        bufferPool: AudioBufferPool,
        featureExtractor: AudioFeatureExtractor
    ): AudioProcessingPipeline {
        return AudioProcessingPipeline(bufferPool, featureExtractor)
    }
}

Performance Optimization Strategies

Memory Management

@Singleton
class AudioBufferPool @Inject constructor() {
    
    private val pool = object : Pools.SynchronizedPool<FloatArray>(10) {
        override fun create(): FloatArray = FloatArray(16000) // 1 second at 16kHz
    }
    
    fun acquire(): FloatArray? = pool.acquire()
    
    fun release(buffer: FloatArray) {
        // Clear buffer for security
        buffer.fill(0f)
        pool.release(buffer)
    }
    
    fun getPoolStatus(): PoolStatus {
        return PoolStatus(
            totalCapacity = 10,
            availableBuffers = pool.size,
            bufferSize = 16000
        )
    }
}

Battery Optimization

@Singleton
class PowerOptimizedAnalyzer @Inject constructor(
    private val powerManager: PowerManager,
    private val batteryManager: BatteryManager
) {
    
    fun shouldPerformAnalysis(): Boolean {
        val batteryLevel = batteryManager.getIntProperty(BatteryManager.BATTERY_PROPERTY_CAPACITY)
        val isPowerSaveMode = powerManager.isPowerSaveMode
        
        return when {
            batteryLevel < 10 -> false // Critical battery
            isPowerSaveMode -> false // Power save mode
            batteryLevel < 25 -> useReducedProcessing() // Limited processing
            else -> true // Full analysis
        }
    }
    
    private fun useReducedProcessing(): Boolean {
        // Use CPU-only processing instead of NPU to save power
        return true
    }
}

Privacy and Security Implementation

@Singleton
class PrivacyController @Inject constructor(
    private val encryptionManager: EncryptionManager,
    private val auditLogger: PrivacyAuditLogger
) {
    
    private val _consentState = MutableStateFlow(GDPRConsentState())
    val consentState: StateFlow<GDPRConsentState> = _consentState.asStateFlow()
    
    fun updateConsent(consentType: ConsentType, granted: Boolean) {
        val currentState = _consentState.value
        val updatedState = when (consentType) {
            ConsentType.VOICE_ANALYSIS -> currentState.copy(voiceAnalysisConsent = granted)
            ConsentType.DATA_ANALYTICS -> currentState.copy(dataAnalyticsConsent = granted)
            ConsentType.AI_RECOMMENDATIONS -> currentState.copy(aiRecommendationsConsent = granted)
            ConsentType.RESEARCH_PARTICIPATION -> currentState.copy(researchParticipation = granted)
        }
        
        _consentState.value = updatedState
        
        // Log consent change for audit
        auditLogger.logConsentChange(
            consentType = consentType,
            granted = granted,
            timestamp = System.currentTimeMillis(),
            ipAddress = getCurrentIPAddress()
        )
    }
    
    fun validateAnalysisPermissions(context: StressAnalysisContext) {
        val consent = _consentState.value
        
        if (!consent.voiceAnalysisConsent) {
            throw PrivacyException("Voice analysis consent not granted")
        }
        
        if (context.requiresDataSharing && !consent.dataAnalyticsConsent) {
            throw PrivacyException("Data analytics consent required for this operation")
        }
    }
    
    suspend fun processDataSubjectRequest(request: DataSubjectRequest): DataSubjectResponse {
        return when (request.type) {
            DataSubjectRequestType.ACCESS -> {
                // Article 15 - Right of access
                val personalData = collectPersonalData(request.userId)
                DataSubjectResponse.AccessResponse(personalData)
            }
            DataSubjectRequestType.RECTIFICATION -> {
                // Article 16 - Right to rectification
                rectifyPersonalData(request.userId, request.corrections)
                DataSubjectResponse.RectificationResponse()
            }
            DataSubjectRequestType.ERASURE -> {
                // Article 17 - Right to erasure
                erasePersonalData(request.userId)
                DataSubjectResponse.ErasureResponse()
            }
            DataSubjectRequestType.PORTABILITY -> {
                // Article 20 - Right to data portability
                val portableData = exportPortableData(request.userId)
                DataSubjectResponse.PortabilityResponse(portableData)
            }
        }
    }
}

Testing Strategy

Unit Testing

@RunWith(JUnit4::class)
class ECAPAStressEngineTest {
    
    @Mock
    private lateinit var npuDelegate: NPUDelegate
    
    @Mock
    private lateinit var modelCache: ModelCache
    
    @Mock
    private lateinit var performanceMonitor: PerformanceMonitor
    
    private lateinit var ecapaEngine: ECAPAStressEngine
    
    @Before
    fun setup() {
        MockitoAnnotations.openMocks(this)
        ecapaEngine = ECAPAStressEngine(npuDelegate, modelCache, performanceMonitor)
    }
    
    @Test
    fun `extract stress embeddings returns correct dimensions`() = runTest {
        // Given
        val mfccFeatures = FloatArray(39 * 100) { Random.nextFloat() } // 100 frames, 39 MFCC
        `when`(npuDelegate.isNPUAvailable()).thenReturn(true)
        
        // When
        val embeddings = ecapaEngine.extractStressEmbeddings(mfccFeatures)
        
        // Then
        assertEquals(192, embeddings.size) // ECAPA-TDNN embedding dimension
        assertTrue(embeddings.all { !it.isNaN() })
    }
    
    @Test
    fun `classify stress returns valid stress level`() = runTest {
        // Given
        val embeddings = FloatArray(192) { Random.nextFloat() }
        
        // When
        val classification = ecapaEngine.classifyStress(embeddings)
        
        // Then
        assertTrue(classification.level in 1..10)
        assertTrue(classification.confidence in 0f..1f)
    }
}

Integration Testing

@RunWith(AndroidJUnit4::class)
@HiltAndroidTest
class StressAnalysisIntegrationTest {
    
    @get:Rule
    var hiltRule = HiltAndroidRule(this)
    
    @Inject
    lateinit var stressAnalysisManager: StressAnalysisManager
    
    @Before
    fun setup() {
        hiltRule.inject()
    }
    
    @Test
    fun `end to end stress analysis completes successfully`() = runTest {
        // Given
        val testAudioData = loadTestAudioFile("test_stressed_voice.wav")
        val context = StressAnalysisContext(
            userId = "test_user",
            sessionId = "test_session",
            environmentContext = "office"
        )
        
        // When
        val result = stressAnalysisManager.performStressAnalysis(testAudioData, context)
        
        // Then
        assertNotNull(result)
        assertTrue(result.level in 1..10)
        assertTrue(result.confidence > 0.5f)
        assertTrue(result.processingTimeMs < 3000) // Under 3 seconds
        assertNotNull(result.recommendations)
        assertTrue(result.recommendations.isNotEmpty())
    }
}

Deployment and Distribution

Build Configuration

// app/build.gradle.kts
android {
    compileSdk 34
    
    defaultConfig {
        applicationId = "com.stressless.android"
        minSdk = 26 // Android 8.0 (required for NNAPI)
        targetSdk = 34
        
        testInstrumentationRunner = "com.stressless.HiltTestRunner"
    }
    
    buildTypes {
        release {
            isMinifyEnabled = true
            isShrinkResources = true
            proguardFiles(
                getDefaultProguardFile("proguard-android-optimize.txt"),
                "proguard-rules.pro"
            )
        }
    }
    
    packaging {
        resources {
            excludes.addAll(listOf(
                "META-INF/DEPENDENCIES",
                "META-INF/LICENSE",
                "META-INF/LICENSE.txt",
                "META-INF/NOTICE",
                "META-INF/NOTICE.txt"
            ))
        }
    }
}

dependencies {
    // Core Android
    implementation("androidx.core:core-ktx:1.12.0")
    implementation("androidx.lifecycle:lifecycle-runtime-ktx:2.7.0")
    
    // Jetpack Compose
    implementation("androidx.activity:activity-compose:1.8.2")
    implementation("androidx.compose.ui:ui:$composeVersion")
    implementation("androidx.compose.material3:material3:1.1.2")
    
    // LiteRT (formerly TensorFlow Lite)
    implementation("com.google.ai.edge.litert:litert:1.0.1")
    implementation("com.google.ai.edge.litert:litert-gpu:1.0.1")
    implementation("com.google.ai.edge.litert:litert-support:1.0.1")
    
    // Qualcomm NPU support
    implementation("com.qualcomm.qti:qnn-litert-delegate:2.34.0")
    
    // Database and encryption
    implementation("androidx.room:room-runtime:2.6.1")
    implementation("androidx.room:room-ktx:2.6.1")
    implementation("net.zetetic:android-database-sqlcipher:4.5.4")
    
    // Dependency injection
    implementation("com.google.dagger:hilt-android:2.48.1")
    kapt("com.google.dagger:hilt-compiler:2.48.1")
    
    // Audio processing
    implementation("be.tarsos.dsp:core:2.4")
    implementation("be.tarsos.dsp:jvm:2.4")
    
    // Privacy and security
    implementation("androidx.security:security-crypto:1.1.0-alpha06")
    
    // Background work
    implementation("androidx.work:work-runtime-ktx:2.9.0")
    
    // Testing
    testImplementation("junit:junit:4.13.2")
    testImplementation("org.mockito:mockito-core:5.5.0")
    testImplementation("org.jetbrains.kotlinx:kotlinx-coroutines-test:1.7.3")
    
    androidTestImplementation("androidx.test.ext:junit:1.1.5")
    androidTestImplementation("androidx.compose.ui:ui-test-junit4:$composeVersion")
    androidTestImplementation("com.google.dagger:hilt-android-testing:2.48.1")
}

Performance Benchmarks and Targets

Performance Requirements

Metric	Target	Measurement Method
Voice Analysis Time	<3 seconds	End-to-end processing time
NPU Initialization	<500ms	Model loading and setup
Memory Usage	<200MB	Peak RAM during analysis
Battery Impact	<2% per analysis	Power consumption measurement
Storage Efficiency	<50MB app size	APK size optimization

NPU Performance Matrix

Chipset	Expected Performance	Fallback Strategy
Snapdragon 8 Elite	<1 second analysis	GPU → CPU
Snapdragon 8 Gen 3	<1.5 seconds	GPU → CPU
MediaTek Dimensity 9400	<2 seconds	GPU → CPU
Exynos 2400	<2.5 seconds	GPU → CPU
CPU Only	<5 seconds	Optimized CPU processing

Conclusion

This architecture provides a robust, scalable, and privacy-first foundation for the StressLess Android application using SpeechBrain ECAPA-TDNN as the primary voice analysis engine. The design emphasizes:

NPU-First Performance: Optimal hardware utilization for sub-3-second analysis
Privacy by Design: Complete local processing with GDPR compliance
Commercial Viability: Apache 2.0 and MIT licensed components throughout
Production Readiness: Comprehensive testing, monitoring, and deployment strategies
Scalable Architecture: Clean separation of concerns enabling future enhancements

The implementation leverages modern Android development practices (Jetpack Compose, Hilt, Room) while maintaining enterprise-grade security and clinical-level accuracy for workplace stress monitoring applications.

21 September 2025